On the public citation graph

Deep features for breast cancer histopathological image classification

https://doi.org/10.1109/smc.2017.8122889
0 signed · 333 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-642-13131-8_4openalex-snapshot
Structured Literature Image Finder: Extracting Information from Text and Images in Biomedical Literature
inferredcites →https://doi.org/10.1007/s00138-012-0459-8openalex-snapshot
Breast cancer diagnosis from biopsy images with highly reliable random subspace classifier ensembles
inferredcites →https://doi.org/10.1007/s11263-015-0872-3openalex-snapshot
Deep Filter Banks for Texture Recognition, Description, and Segmentation
inferredcites →https://doi.org/10.1016/j.compbiomed.2013.08.003openalex-snapshot
Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images
inferredcites →https://doi.org/10.1109/cvpr.2009.5206848openalex-snapshot
ImageNet: A large-scale hierarchical image database
inferredcites →https://doi.org/10.1109/cvprw.2014.131openalex-snapshot
CNN Features Off-the-Shelf: An Astounding Baseline for Recognition
inferredcites →https://doi.org/10.1109/icpr.2014.199openalex-snapshot
Forest Species Recognition Using Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/icpr.2016.7900002openalex-snapshot
Deep learning for magnification independent breast cancer histopathology image classification
inferredcites →https://doi.org/10.1109/ijcnn.2016.7727519openalex-snapshot
Breast cancer histopathological image classification using Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/isbi.2008.4541041openalex-snapshot
Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features
inferredcites →https://doi.org/10.1109/jsyst.2013.2279415openalex-snapshot
Remote Computer-Aided Breast Cancer Detection and Diagnosis System Based on Cytological Images
inferredcites →https://doi.org/10.1109/tbme.2015.2496264openalex-snapshot
A Dataset for Breast Cancer Histopathological Image Classification
inferredcites →https://doi.org/10.1109/tmi.2013.2275151openalex-snapshot
Computer-Aided Breast Cancer Diagnosis Based on the Analysis of Cytological Images of Fine Needle Biopsies
inferredcites →https://doi.org/10.1109/tmi.2016.2528162openalex-snapshot
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
inferredcites →https://doi.org/10.1109/tpami.2002.1017623openalex-snapshot
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
inferredcites →https://doi.org/10.1109/tpami.2013.50openalex-snapshot
Representation Learning: A Review and New Perspectives
inferredcites →https://doi.org/10.1145/2480362.2480368openalex-snapshot
A multiple feature vector framework for forest species recognition
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1186/1471-2105-8-110openalex-snapshot
Fast automated cell phenotype image classification
inferredcites →https://doi.org/10.1186/1687-6180-2014-17openalex-snapshot
One-class kernel subspace ensemble for medical image classification
inferredcites →https://doi.org/10.4103/2153-3539.153906openalex-snapshot
2014 American Telemedicine Association clinical guidelines for telepathology: Another important step in support of increased adoption of telepathology for patient care
inferredcites →https://doi.org/10.48550/arxiv.1310.1531openalex-snapshot
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.3978707openalex-extracted
MixPatch: A New Method for Training Histopathology Image Classifiers
inferred← citeshttps://doi.org/10.2139/ssrn.4017036openalex-extracted
Deep and Dense Convolutional Neural Network ( D2 CN2 for Multi Category Classification of Magnification Specific and Magnification Independent Breast Cancer Histopathological Images
inferred← citeshttps://doi.org/10.1002/appl.70021openalex-snapshot
Wavelet‐Enhanced Deformable Convolutional Network for Breast Cancer Classification in High‐Resolution Histopathology Images
inferred← citeshttps://doi.org/10.1002/ima.22309openalex-snapshot
Cell‐type based semantic segmentation of histopathological images using deep convolutional neural networks
inferred← citeshttps://doi.org/10.1002/ima.22399openalex-snapshot
Pre‐trained convolutional neural networks as feature extractors for diagnosis of breast cancer using histopathology
inferred← citeshttps://doi.org/10.1002/ima.22403openalex-snapshot
Residual learning based CNN for breast cancer histopathological image classification
inferred← citeshttps://doi.org/10.1002/ima.22465openalex-snapshot
Breast cancer histopathology image classification using kernelized weighted extreme learning machine
inferred← citeshttps://doi.org/10.1002/ima.22548openalex-snapshot
Classification of breast cancer histopathological image with deep residual learning
inferred← citeshttps://doi.org/10.1002/ima.22628openalex-snapshot
Breast cancer histopathological image classification using attention high‐order deep network
inferred← citeshttps://doi.org/10.1002/ima.22698openalex-snapshot
Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network
inferred← citeshttps://doi.org/10.1002/ima.23082openalex-snapshot
EENet : Application of convolutional neural network‐based deep learning methods in bone tumor pathological diagnosis
inferred← citeshttps://doi.org/10.1002/jemt.24054openalex-snapshot
Breast microscopic cancer segmentation and classification using unique 4‐qubit ‐quantum model
inferred← citeshttps://doi.org/10.1007/978-3-030-01421-6_11openalex-snapshot
Breast Cancer Histopathological Image Classification via Deep Active Learning and Confidence Boosting
inferred← citeshttps://doi.org/10.1007/978-3-030-04946-1_10openalex-snapshot
Multi-task Deep Learning for Fine-Grained Classification/Grading in Breast Cancer Histopathological Images
inferred← citeshttps://doi.org/10.1007/978-3-030-17938-0_19openalex-snapshot
Classifying Breast Cancer Histopathological Images Using a Robust Artificial Neural Network Architecture
inferred← citeshttps://doi.org/10.1007/978-3-030-23762-2_20openalex-snapshot
A Survey for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-38364-0_23openalex-snapshot
Fusing of Deep Learning, Transfer Learning and GAN for Breast Cancer Histopathological Image Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-41005-6_18openalex-snapshot
Assessing the Impact of a Preprocessing Stage on Deep Learning Architectures for Breast Tumor Multi-class Classification with Histopathological Images
inferred← citeshttps://doi.org/10.1007/978-3-030-49345-5_24openalex-snapshot
Computer Aided System for Nuclei Localization in Histopathological Images Using CNN
inferred← citeshttps://doi.org/10.1007/978-3-030-61401-0_45openalex-snapshot
Breast Cancer Classification from Histopathological Images Using Transfer Learning and Deep Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-63830-6_26openalex-snapshot
Encoder-Decoder Based CNN Structure for Microscopic Image Identification
inferred← citeshttps://doi.org/10.1007/978-3-030-96302-6_52openalex-snapshot
Malignancy Detection in Breast Histo-Images Using Multi-layer Perceptron
inferred← citeshttps://doi.org/10.1007/978-3-031-07750-0_30openalex-snapshot
A Lightweight Convolutional Neural Network for Breast Cancer Diagnosis with Histology Images
inferred← citeshttps://doi.org/10.1007/978-3-031-46664-9_15openalex-snapshot
Breast Cancer Histopathology Image Classification Using Frequency Attention Convolution Network
inferred← citeshttps://doi.org/10.1007/978-3-031-66410-6_25openalex-snapshot
UDR Fused Multimodal Approach for Disease Classification in Large Scale Dataset with Advanced CNNs
inferred← citeshttps://doi.org/10.1007/978-3-031-66842-5_8openalex-snapshot
Leveraging Deep Embeddings for Explainable Medical Image Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-73967-5_3openalex-snapshot
TopOC: Topological Deep Learning for Ovarian and Breast Cancer Diagnosis
inferred← citeshttps://doi.org/10.1007/978-3-031-77620-5_3openalex-snapshot
Automatic Invasive Ductal Carcinoma Detection Using Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-031-90714-2_6openalex-snapshot
Transformers for Interpretable Classification of Histopathological Images
inferred← citeshttps://doi.org/10.1007/978-3-319-78759-6_26openalex-snapshot
Classification of Breast Cancer Histopathological Images Using KAZE Features
inferred← citeshttps://doi.org/10.1007/978-3-319-93000-8_82openalex-snapshot
Towards Interactive Breast Tumor Classification Using Transfer Learning
inferred← citeshttps://doi.org/10.1007/978-3-319-93000-8_94openalex-snapshot
Breast Cancer Histology Image Classification Based on Deep Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-319-95957-3_38openalex-snapshot
Histopathological Image Recognition with Domain Knowledge Based Deep Features
inferred← citeshttps://doi.org/10.1007/978-981-13-3140-4_69openalex-snapshot
Automatic Magnification Independent Classification of Breast Cancer Tissue in Histological Images Using Deep Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/978-981-15-3242-9_64openalex-snapshot
Juxtaposing Deep Learning Architectures for Breast Cancer Classification
inferred← citeshttps://doi.org/10.1007/978-981-16-1244-2_7openalex-snapshot
Breast Cancer Detection in Histology Images Using Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/978-981-16-1249-7_27openalex-snapshot
Various Image Modalities Used in Computer-Aided Diagnosis System for Detection of Breast Cancer Using Machine Learning Techniques: A Systematic Review
inferred← citeshttps://doi.org/10.1007/978-981-16-1681-5_14openalex-snapshot
Automatic Deep Learning Framework for Breast Cancer Detection and Classification from H&E Stained Breast Histopathology Images
inferred← citeshttps://doi.org/10.1007/978-981-16-5301-8_37openalex-snapshot
Review of Deep Learning and Interpretability
inferred← citeshttps://doi.org/10.1007/978-981-19-0604-6_42openalex-snapshot
An Elaborative Approach for the Histopathological Classification of the Breast Cancer using Residual Neural Networks
inferred← citeshttps://doi.org/10.1007/978-981-19-2456-9_93openalex-snapshot
Machine Learning in Medical Image Processing
inferred← citeshttps://doi.org/10.1007/978-981-19-4960-9_11openalex-snapshot
Study of Identification of Breast Tumor Through DL Technique
inferred← citeshttps://doi.org/10.1007/978-981-19-6901-0_62openalex-snapshot
Improved Res2Net Based on Multi-scale Attention Mechanism for Breast Cancer Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-19-7402-1_51openalex-snapshot
Machine Learning Techniques for Automated Nuclear Atypia Detection in Histopathology Images: A Review
inferred← citeshttps://doi.org/10.1007/978-981-19-8825-7_51openalex-snapshot
A Shallow Convolutional Neural Network Model for Breast Cancer Histopathology Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-33-4968-1_9openalex-snapshot
Detection of Invasive Ductal Carcinoma from Breast Histopathology Image Using Deep Ensemble Neural Networks
inferred← citeshttps://doi.org/10.1007/978-981-96-6594-5_26openalex-snapshot
CaDT-Net: A Cascaded Deformable Transformer Network for Multiclass Breast Cancer Histopathological Image Classification
inferred← citeshttps://doi.org/10.1007/978-981-96-9771-7_32openalex-snapshot
Optimizing Breast Cancer Detection Using Ensemble Method with Histopathological Images
inferred← citeshttps://doi.org/10.1007/978-981-97-3980-6_53openalex-snapshot
Application of Active Learning Technique with CNN for the Classification of Microscopic Breast Cancer Images
inferred← citeshttps://doi.org/10.1007/978-981-99-1230-8_8openalex-snapshot
Prediction of Breast Cancer Via Deep Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-4914-4_11openalex-snapshot
Classifying Breast Cancer Using Deep Convolutional Neural Network Method
inferred← citeshttps://doi.org/10.1007/s00371-019-01768-6openalex-snapshot
Effect of layer-wise fine-tuning in magnification-dependent classification of breast cancer histopathological image
inferred← citeshttps://doi.org/10.1007/s00521-021-05947-2openalex-snapshot
Deep assisted dense model based classification of invasive ductal breast histology images
inferred← citeshttps://doi.org/10.1007/s00521-022-07183-8openalex-snapshot
Detection of ring cell cancer in histopathological images with region of interest determined by SLIC superpixels method
inferred← citeshttps://doi.org/10.1007/s00521-024-10464-zopenalex-snapshot
Enhancing breast cancer histopathological image classification using attention-based high order covariance pooling
inferred← citeshttps://doi.org/10.1007/s00530-024-01349-1openalex-snapshot
A review of deep learning and Generative Adversarial Networks applications in medical image analysis
inferred← citeshttps://doi.org/10.1007/s10278-019-00182-7openalex-snapshot
Breast Cancer Classification from Histopathological Images with Inception Recurrent Residual Convolutional Neural Network
inferred← citeshttps://doi.org/10.1007/s10278-019-00295-zopenalex-snapshot
Computer-Aided Histopathological Image Analysis Techniques for Automated Nuclear Atypia Scoring of Breast Cancer: a Review
inferred← citeshttps://doi.org/10.1007/s10278-019-00307-yopenalex-snapshot
Conventional Machine Learning and Deep Learning Approach for Multi-Classification of Breast Cancer Histopathology Images—a Comparative Insight
inferred← citeshttps://doi.org/10.1007/s10278-023-00887-wopenalex-snapshot
Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis
inferred← citeshttps://doi.org/10.1007/s10462-019-09716-5openalex-snapshot
Deep learning-based breast cancer classification through medical imaging modalities: state of the art and research challenges
inferred← citeshttps://doi.org/10.1007/s10462-024-10963-4openalex-snapshot
Mises-Fisher similarity-based boosted additive angular margin loss for breast cancer classification
inferred← citeshttps://doi.org/10.1007/s10549-023-06970-8openalex-snapshot
Classification of breast tumors by using a novel approach based on deep learning methods and feature selection
inferred← citeshttps://doi.org/10.1007/s11042-018-6970-9openalex-snapshot
Multi-task deep learning for fine-grained classification and grading in breast cancer histopathological images
inferred← citeshttps://doi.org/10.1007/s11042-019-7468-9openalex-snapshot
Breast cancer classification in pathological images based on hybrid features
inferred← citeshttps://doi.org/10.1007/s11042-019-7525-4openalex-snapshot
Breast Cancer Multi-classification through Deep Neural Network and Hierarchical Classification Approach
inferred← citeshttps://doi.org/10.1007/s11042-020-08692-1openalex-snapshot
Ensembled deep convolution neural network-based breast cancer classification with misclassification reduction algorithms
inferred← citeshttps://doi.org/10.1007/s11042-021-11199-yopenalex-snapshot
BrC-MCDLM: breast Cancer detection using Multi-Channel deep learning model
inferred← citeshttps://doi.org/10.1007/s11042-021-11775-2openalex-snapshot
Breast cancer detection from histopathology images with deep inception and residual blocks
inferred← citeshttps://doi.org/10.1007/s11042-021-11853-5openalex-snapshot
A deep learning based approach to detect IDC in histopathology images
inferred← citeshttps://doi.org/10.1007/s11042-022-13119-0openalex-snapshot
ExpertosLF: dynamic late fusion of CBIR systems using online learning with relevance feedback
inferred← citeshttps://doi.org/10.1007/s11042-024-19685-9openalex-snapshot
Magnification Independent Breast Cancer Analysis Using Vision Transformer
inferred← citeshttps://doi.org/10.1007/s11042-025-20766-6openalex-snapshot
A segmentation-free method for image retrieval and pattern spotting in historical documents using convolutional features
inferred← citeshttps://doi.org/10.1007/s11063-022-11114-yopenalex-snapshot
Cancer Identification in Enteric Nervous System Preclinical Images Using Handcrafted and Automatic Learned Features
inferred← citeshttps://doi.org/10.1007/s11633-019-1210-yopenalex-snapshot
Generalized Multiscale RBF Networks and the DCT for Breast Cancer Detection
inferred← citeshttps://doi.org/10.1007/s11760-022-02263-7openalex-snapshot
Magnification-specific and magnification-independent classification of breast cancer histopathological image using deep learning approaches
inferred← citeshttps://doi.org/10.1007/s11760-023-02587-yopenalex-snapshot
Histopathological image classification using CNN with squeeze and excitation networks based on hybrid squeezing
inferred← citeshttps://doi.org/10.1007/s11760-025-04122-7openalex-snapshot
Deep learning-based histopathological classification of breast tumors: a multi-magnification approach with state-of-the-art models
inferred← citeshttps://doi.org/10.1007/s11761-023-00378-4openalex-snapshot
A computer-aided diagnosis system for breast pathology: a deep learning approach with model interpretability from pathological perspective
inferred← citeshttps://doi.org/10.1007/s11831-020-09470-wopenalex-snapshot
Breast Cancer Detection, Segmentation and Classification on Histopathology Images Analysis: A Systematic Review
inferred← citeshttps://doi.org/10.1007/s11831-025-10323-7openalex-snapshot
Applications of GAN Models in Breast Cancer Detection: A Comprehensive Review
inferred← citeshttps://doi.org/10.1007/s11831-025-10372-yopenalex-snapshot
Breast Cancerous Tumor Classification: A Comparative Analysis of Machine Learning and Deep Learning on Different Datasets
inferred← citeshttps://doi.org/10.1007/s12065-021-00564-3openalex-snapshot
Sub-classification of invasive and non-invasive cancer from magnification independent histopathological images using hybrid neural networks
inferred← citeshttps://doi.org/10.1007/s12257-023-0164-7openalex-snapshot
Convolution Neural Network Approaches for Cancer Cell Image Classification
inferred← citeshttps://doi.org/10.1007/s12539-022-00515-1openalex-snapshot
Feature Generalization for Breast Cancer Detection in Histopathological Images
inferred← citeshttps://doi.org/10.1007/s12539-024-00630-1openalex-snapshot
MetaV: A Pioneer in feature Augmented Meta-Learning Based Vision Transformer for Medical Image Classification
inferred← citeshttps://doi.org/10.1007/s12553-022-00703-5openalex-snapshot
Breast cancer image analysis using deep learning techniques – a survey
inferred← citeshttps://doi.org/10.1007/s42600-024-00370-7openalex-snapshot
Breast cancer histopathology image classification using an ensemble of optimized pretrained models with a trainable ensemble strategy classifier
inferred← citeshttps://doi.org/10.1007/s42979-024-03590-xopenalex-snapshot
Advanced PTSVM Based Breast Cancer Classification with Weighted Feature Selection
inferred← citeshttps://doi.org/10.1007/s44564-026-00013-2openalex-snapshot
A hierarchical pipeline for preprocessing and classification of breast histopathology images into benign and malignant
inferred← citeshttps://doi.org/10.1016/b978-0-12-818146-1.00004-0openalex-snapshot
Transfer Learning and Supervised Classifier Based Prediction Model for Breast Cancer
inferred← citeshttps://doi.org/10.1016/b978-0-443-18450-5.00002-5openalex-snapshot
Diagnosis of breast cancer from histopathological images with deep learning architectures
inferred← citeshttps://doi.org/10.1016/j.artmed.2018.04.005openalex-snapshot
MuDeRN: Multi-category classification of breast histopathological image using deep residual networks
inferred← citeshttps://doi.org/10.1016/j.artmed.2022.102433openalex-snapshot
MF-OMKT: Model fusion based on online mutual knowledge transfer for breast cancer histopathological image classification
inferred← citeshttps://doi.org/10.1016/j.asoc.2021.107886openalex-snapshot
Breast cancer intelligent analysis of histopathological data: A systematic review
inferred← citeshttps://doi.org/10.1016/j.bspc.2019.101582openalex-snapshot
Content-based histopathological image retrieval using multi-scale and multichannel decoder based LTP
inferred← citeshttps://doi.org/10.1016/j.bspc.2020.102192openalex-snapshot
A new transfer learning based approach to magnification dependent and independent classification of breast cancer in histopathological images
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.103451openalex-snapshot
DBLCNN: Dependency-based lightweight convolutional neural network for multi-classification of breast histopathology images
inferred← citeshttps://doi.org/10.1016/j.bspc.2022.103935openalex-snapshot
Deep and dense convolutional neural network for multi category classification of magnification specific and magnification independent breast cancer histopathological images
inferred← citeshttps://doi.org/10.1016/j.bspc.2023.105418openalex-snapshot
A self-learning deep neural network for classification of breast histopathological images
inferred← citeshttps://doi.org/10.1016/j.bspc.2024.106157openalex-snapshot
A novel cross correlation-based color texture descriptor for the classification of breast cancer histopathology images
inferred← citeshttps://doi.org/10.1016/j.bspc.2025.108011openalex-snapshot
An explainable AI for breast cancer classification using vision Transformer (ViT)
inferred← citeshttps://doi.org/10.1016/j.cmpb.2020.105531openalex-snapshot
Computer assisted recognition of breast cancer in biopsy images via fusion of nucleus-guided deep convolutional features
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2020.103954openalex-snapshot
Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2021.104651openalex-snapshot
Multi-channel Chan-Vese model for unsupervised segmentation of nuclei from breast histopathological images
inferred← citeshttps://doi.org/10.1016/j.compmedimag.2021.101870openalex-snapshot
A tree-based multiclassification of breast tumor histopathology images through deep learning
inferred← citeshttps://doi.org/10.1016/j.compmedimag.2021.101922openalex-snapshot
Pattern classification for breast lesion on FFDM by integration of radiomics and deep features
inferred← citeshttps://doi.org/10.1016/j.eswa.2018.09.049openalex-snapshot
Multiple instance learning for histopathological breast cancer image classification
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.115586openalex-snapshot
DeepBatch: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.119972openalex-snapshot
Multiresolution texture analysis of histopathologic images using ecological diversity measures
inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123569openalex-snapshot
RDTNet: A residual deformable attention based transformer network for breast cancer classification
inferred← citeshttps://doi.org/10.1016/j.health.2023.100207openalex-snapshot
A magnification-independent method for breast cancer classification using transfer learning
inferred← citeshttps://doi.org/10.1016/j.imu.2019.100231openalex-snapshot
Cancer diagnosis in histopathological image: CNN based approach
inferred← citeshttps://doi.org/10.1016/j.imu.2021.100616openalex-snapshot
A 3 Tier CNN model with deep discriminative feature extraction for discovering malignant growth in multi-scale histopathology images
inferred← citeshttps://doi.org/10.1016/j.ins.2019.08.072openalex-snapshot
Deep feature learning for histopathological image classification of canine mammary tumors and human breast cancer
inferred← citeshttps://doi.org/10.1016/j.jmir.2019.11.001openalex-snapshot
Machine Learning Methods for Computer-Aided Breast Cancer Diagnosis Using Histopathology: A Narrative Review
inferred← citeshttps://doi.org/10.1016/j.jocs.2024.102324openalex-snapshot
LitefusionNet: Boosting the performance for medical image classification with an intelligent and lightweight feature fusion network
inferred← citeshttps://doi.org/10.1016/j.matpr.2021.03.707openalex-snapshot
Improved the detection and classification of breast cancer using hyper parameter tuning
inferred← citeshttps://doi.org/10.1016/j.media.2019.03.009openalex-snapshot
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
inferred← citeshttps://doi.org/10.1016/j.media.2021.102032openalex-snapshot
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides
inferred← citeshttps://doi.org/10.1016/j.mlwa.2021.100154openalex-snapshot
An investigation of XGBoost-based algorithm for breast cancer classification
inferred← citeshttps://doi.org/10.1016/j.neucom.2019.09.044openalex-snapshot
BreakHis based breast cancer automatic diagnosis using deep learning: Taxonomy, survey and insights
inferred← citeshttps://doi.org/10.1016/j.neucom.2021.07.024openalex-snapshot
Automatic classification method of thyroid pathological images using multiple magnification factors
inferred← citeshttps://doi.org/10.1016/j.patrec.2020.09.020openalex-snapshot
An experimental study on classification of thyroid histopathology images using transfer learning
inferred← citeshttps://doi.org/10.1038/s41467-025-57587-yopenalex-snapshot
A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images
inferred← citeshttps://doi.org/10.1038/s41598-021-86912-wopenalex-snapshot
PathoNet introduced as a deep neural network backend for evaluation of Ki-67 and tumor-infiltrating lymphocytes in breast cancer
inferred← citeshttps://doi.org/10.1038/s41598-025-11816-yopenalex-snapshot
Enhancing breast cancer classification using a deep sparse wavelet autoencoder approach
inferred← citeshttps://doi.org/10.1049/cvi2.12021openalex-snapshot
Going deeper: magnification‐invariant approach for breast cancer classification using histopathological images
inferred← citeshttps://doi.org/10.1049/ipr2.12074openalex-snapshot
Optimised CNN in conjunction with efficient pooling strategy for the multi‐classification of breast cancer
inferred← citeshttps://doi.org/10.1063/5.0235553openalex-snapshot
Breast cancer histopathological images classification based on weighted K-nearest neighbor
inferred← citeshttps://doi.org/10.1080/03091902.2021.1896814openalex-snapshot
Sliding window based deep ensemble system for breast cancer classification
inferred← citeshttps://doi.org/10.1080/03772063.2019.1583610openalex-snapshot
Sliding Window Based Support Vector Machine System for Classification of Breast Cancer Using Histopathological Microscopic Images
inferred← citeshttps://doi.org/10.1101/2025.03.09.642276openalex-snapshot
AGP-Net: A Universal Network for Gene Expression Prediction of Spatial Transcriptomics
inferred← citeshttps://doi.org/10.1109/access.2018.2831280openalex-snapshot
Classification of Breast Cancer Based on Histology Images Using Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/access.2019.2897281openalex-snapshot
Heterogeneity-Aware Local Binary Patterns for Retrieval of Histopathology Images
inferred← citeshttps://doi.org/10.1109/access.2019.2904245openalex-snapshot
Discriminative Pattern Mining for Breast Cancer Histopathology Image Classification via Fully Convolutional Autoencoder
inferred← citeshttps://doi.org/10.1109/access.2020.2993788openalex-snapshot
A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/access.2020.3019327openalex-snapshot
Classification of Breast Cancer Histopathological Images Using Discriminative Patches Screened by Generative Adversarial Networks
inferred← citeshttps://doi.org/10.1109/access.2020.3021557openalex-snapshot
Deep Learning Applied for Histological Diagnosis of Breast Cancer
inferred← citeshttps://doi.org/10.1109/access.2020.3047455openalex-snapshot
Study on the Identification Method of Human Upper Limb Flag Movements Based on Inception-ResNet Double Stream Network
inferred← citeshttps://doi.org/10.1109/access.2021.3071057openalex-snapshot
Research on the Auxiliary Classification and Diagnosis of Lung Cancer Subtypes Based on Histopathological Images
inferred← citeshttps://doi.org/10.1109/access.2022.3163822openalex-snapshot
Breast Cancer Classification From Histopathological Images Using Resolution Adaptive Network
inferred← citeshttps://doi.org/10.1109/access.2023.3245023openalex-snapshot
Modality Specific CBAM-VGGNet Model for the Classification of Breast Histopathology Images via Transfer Learning
inferred← citeshttps://doi.org/10.1109/access.2023.3314978openalex-snapshot
Brea-Net: An Interpretable Dual-Attention Network for Imbalanced Breast Cancer Classification
inferred← citeshttps://doi.org/10.1109/access.2023.3347339openalex-snapshot
Discriminative Dictionary Learning Using Penalized Rank-1 Approximation for Breast Cancer Classification With Imbalanced Dataset
inferred← citeshttps://doi.org/10.1109/access.2024.3386355openalex-snapshot
A Comprehensive Study on Classification of Breast Cancer Histopathological Images: Binary Versus Multi-Category and Magnification-Specific Versus Magnification-Independent
inferred← citeshttps://doi.org/10.1109/access.2024.3411633openalex-snapshot
Cancer Disease Prediction Using Integrated Smart Data Augmentation and Capsule Neural Network
inferred← citeshttps://doi.org/10.1109/access.2025.3598450openalex-snapshot
BreNet: Attention-Enhanced Multi-Scale CNN Framework for Breast Cancer Classification in Histopathological Images
inferred← citeshttps://doi.org/10.1109/accthpa49271.2020.9213192openalex-snapshot
A Deep CNN Technique for Detection of Breast Cancer Using Histopathology Images
inferred← citeshttps://doi.org/10.1109/aect47998.2020.9194194openalex-snapshot
Automatic Breast Cancer Classification from Histopathological Images
inferred← citeshttps://doi.org/10.1109/bibe50027.2020.00153openalex-snapshot
A State-of-the-art Deep Transfer Learning-Based Model for Accurate Breast Cancer Recognition in Histology Images
inferred← citeshttps://doi.org/10.1109/cbms.2019.00120openalex-snapshot
Texture CNN for Histopathological Image Classification
inferred← citeshttps://doi.org/10.1109/cei57409.2022.9950147openalex-snapshot
Comparison of Convolutional Neural Network and Capsule Network in Image Recognition- A Case Study of Microbiopsy Images of Breast Tumor
inferred← citeshttps://doi.org/10.1109/cicn67655.2025.11367996openalex-snapshot
Breast Cancer Diagnosis: Detection and Classification Using DeepSight
inferred← citeshttps://doi.org/10.1109/compsac51774.2021.00249openalex-snapshot
Vision-based Hand Gesture Recognition for Human-Computer Interaction using MobileNetV2
inferred← citeshttps://doi.org/10.1109/conecct52877.2021.9622691openalex-snapshot
Breast Histopathological Image Classification Using Deep Learning
inferred← citeshttps://doi.org/10.1109/conit51480.2021.9498367openalex-snapshot
Deep Learning Based Automated tool for cancer diagnosis from bone histopathology images
inferred← citeshttps://doi.org/10.1109/cvidl51233.2020.00033openalex-snapshot
A Classification Method of Breast Pathological Image Based on Residual Learning
inferred← citeshttps://doi.org/10.1109/dasa59624.2023.10286677openalex-snapshot
Significant Feature Dimensionality Reduction for Histopathology Image Retrieval as a Tool for Healthcare Decisions Support
inferred← citeshttps://doi.org/10.1109/delcon64804.2024.10866971openalex-snapshot
An ML Based Framework for Classification of Breast Histopathological Images Using Fused Feature Set
inferred← citeshttps://doi.org/10.1109/ecce57851.2023.10101642openalex-snapshot
Classification of Breast Tumor Using Radon Cumulative Distribution Transform Nearest Subspace Classifier
inferred← citeshttps://doi.org/10.1109/ecce64574.2025.11013095openalex-snapshot
A Hybrid ViT-GRU Model for Breast Cancer Detection: Addressing Class Imbalance Challenges
inferred← citeshttps://doi.org/10.1109/embc44109.2020.9176594openalex-snapshot
Convolutional Neural Network Based Breast Cancer Histopathology Image Classification
inferred← citeshttps://doi.org/10.1109/embc46164.2021.9630678openalex-snapshot
Breast Cancer Histopathological Image Classification with Adversarial Image Synthesis
inferred← citeshttps://doi.org/10.1109/i-smac47947.2019.9032542openalex-snapshot
Retracted: Bosom Malignant Diseases (Cancer) Identification by using Deep Learning Technique
inferred← citeshttps://doi.org/10.1109/icac3n56670.2022.10074159openalex-snapshot
Magnification independent fine-tuned transfer learning adaptation for multi-classification of breast cancer in histopathology images
inferred← citeshttps://doi.org/10.1109/icacci.2018.8554428openalex-snapshot
Deep PCANet Framework for the Binary Categorization of Breast Histopathology Images
inferred← citeshttps://doi.org/10.1109/icaibd69640.2026.11637336openalex-snapshot
Breast Cancer Classification from Histopathological Images Using Supervised and Unsupervised Machine Learning
inferred← citeshttps://doi.org/10.1109/icassp.2019.8683856openalex-snapshot
Diving Deep onto Discriminative Ensemble of Histological Hashing & Class-Specific Manifold Learning for Multi-class Breast Carcinoma Taxonomy
inferred← citeshttps://doi.org/10.1109/icbdaa.2017.8284105openalex-snapshot
Comparison of deep learning architectures for H&E histopathology images
inferred← citeshttps://doi.org/10.1109/iccda64887.2024.10867378openalex-snapshot
Detection of Cancer Cells Using Convolutional Neural Networks (CNNs)
inferred← citeshttps://doi.org/10.1109/icce48956.2021.9352142openalex-snapshot
Accuracy Improvement in Binary and Multi-Class Classification of Breast Histopathology Images
inferred← citeshttps://doi.org/10.1109/icceic54227.2021.00027openalex-snapshot
Predicting Differentiation Degree of Gastric Cancer Pathology Images Based on Mask Attention R-CNN
inferred← citeshttps://doi.org/10.1109/iccit60459.2023.10441273openalex-snapshot
Breast Cancer Histopathological Image Classification Using an Ensemble of Deep Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/icdmw.2018.00104openalex-snapshot
Grading Tumor Malignancy via Deep Bidirectional LSTM on Graph Manifold Encoded Histopathological Image
inferred← citeshttps://doi.org/10.1109/iceca.2018.8474739openalex-snapshot
Automated Diagnosis of Breast Cancer Using Wavelet Based Entropy Features
inferred← citeshttps://doi.org/10.1109/icecct56650.2023.10179826openalex-snapshot
Novel Neural Network for Breast Cancer Diagnosis
inferred← citeshttps://doi.org/10.1109/icngis54955.2022.10079781openalex-snapshot
Detection of Breast Cancer from Histopathological Images
inferred← citeshttps://doi.org/10.1109/icpcsn58827.2023.00113openalex-snapshot
Grade Classifcation of Breast Cancer using Deep-Learning
inferred← citeshttps://doi.org/10.1109/icrcicn68210.2025.11364738openalex-snapshot
ADGA-NAS: Auto-Diversified Genetic Algorithm Based Neural Architecture Search Framework for Automated Classification of Breast Cancer
inferred← citeshttps://doi.org/10.1109/icspcs50536.2020.9310066openalex-snapshot
Accuracy Improvement in Detection of COVID-19 in Chest Radiography
inferred← citeshttps://doi.org/10.1109/icspis68676.2025.11551687openalex-snapshot
B-CAD: Adaptive Dual-Attention Enhanced Framework for Breast Cancer Histopathology Image Classification
inferred← citeshttps://doi.org/10.1109/icsses62373.2024.10561349openalex-snapshot
DICNet: A Novel CNN Model based on DenseNet with Interleaved Convolutional Block Attention Module for the Classification of Breast Cancer Histopathology Images
inferred← citeshttps://doi.org/10.1109/idap.2018.8620802openalex-snapshot
DEEP LEARNING APPROACH FOR CLASSIFICATION OF BREAST CANCER
inferred← citeshttps://doi.org/10.1109/ijcnn.2019.8852092openalex-snapshot
Double Transfer Learning for Breast Cancer Histopathologic Image Classification
inferred← citeshttps://doi.org/10.1109/ijcnn48605.2020.9206855openalex-snapshot
Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blending
inferred← citeshttps://doi.org/10.1109/ijcnn48605.2020.9207604openalex-snapshot
Breast Cancer Histopathological Image Classification Based on Deep Second-order Pooling Network
inferred← citeshttps://doi.org/10.1109/incacct61598.2024.10551068openalex-snapshot
Hybrid Deep Learning based Multi-Classification of Breast Cancer Approach using Histology Images
inferred← citeshttps://doi.org/10.1109/indicon.2017.8487730openalex-snapshot
Breast Epithelial Duct Region Segmentation Using Intuitionistic Fuzzy Based Multi-Texture Image Map
inferred← citeshttps://doi.org/10.1109/indicon56171.2022.10040127openalex-snapshot
Voting Ensemble SVM Model for Deep CNN Based Breast Histopathology Classification
inferred← citeshttps://doi.org/10.1109/ipta.2019.8936087openalex-snapshot
Challenges and Recent Solutions for Image Segmentation in the Era of Deep Learning
inferred← citeshttps://doi.org/10.1109/isbi.2019.8759454openalex-snapshot
Look, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification
inferred← citeshttps://doi.org/10.1109/iscon47742.2019.9036160openalex-snapshot
Breast Cancer Histopathology Image Classification using AlexNet
inferred← citeshttps://doi.org/10.1109/iscon57294.2023.10111983openalex-snapshot
Breast Cancer Histopathology Image Classification using ADAptive Moment (ADAM) optimization Estimation
inferred← citeshttps://doi.org/10.1109/isdfs55398.2022.9800813openalex-snapshot
A Novel Deep Feature Extraction Engineering for Subtypes of Breast Cancer Diagnosis: A Transfer Learning Approach
inferred← citeshttps://doi.org/10.1109/jbhi.2018.2885134openalex-snapshot
Label-Efficient Breast Cancer Histopathological Image Classification
inferred← citeshttps://doi.org/10.1109/jbhi.2023.3256974openalex-snapshot
Federated Fusion of Magnified Histopathological Images for Breast Tumor Classification in the Internet of Medical Things
inferred← citeshttps://doi.org/10.1109/nssmic.2018.8824722openalex-snapshot
A Deep Features-based Radiomics Model for Breast Lesion Classification on FFDM
inferred← citeshttps://doi.org/10.1109/seeda-cecnsm57760.2022.9932898openalex-snapshot
Breast Cancer Classification of Histopathological Images using Deep Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/smc53654.2022.9945092openalex-snapshot
Towards the Interpretation of Convolutional Neural Networks for Image Classification Using Fuzzy Sets
showing the first 200 of 311
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.