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Transfer Learning with Deep Convolutional Neural Networks for Classifying Cellular Morphological Changes

https://doi.org/10.1177/2472555218818756
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What this work says

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

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Transfer Learning for Cell Nuclei Classification in Histopathology Images
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Deep learning
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Variational Inference: A Review for Statisticians
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Pipeline for illumination correction of images for high‐throughput microscopy
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High-Content Phenotypic Profiling of Drug Response Signatures across Distinct Cancer Cells
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CellProfiler: image analysis software for identifying and quantifying cell phenotypes
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Variational Inference: A Review for Statisticians

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Deep-Learning Models for Lipid Nanoparticle-Based Drug Delivery
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Perbandingan Convolutional Neural Network pada Transfer Learning Method untuk Mengklasifikasikan Sel Darah Putih
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Pengenalan Aktivitas Manusia Melalui Analisis Data Gerakan Smartphone
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ActiveCrowds: A Human-in-the-Loop Machine Learning Framework
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Drug Response Prediction of Liver Cancer Cell Line Using Deep Learning
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Combining CNN and Grad-Cam for COVID-19 Disease Prediction and Visual Explanation
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Deep Transfer Learning for Detecting Covid-19, Pneumonia and Tuberculosis Using Cxr Images – A Review
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Inference From Complex Networks: Role of Symmetry and Applicability to Images
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Morphologic identification of clinically encountered moulds using a residual neural network
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HoloMoA: a holography and deep learning tool for the identification of antimicrobial mechanisms of action and the detection of novel MoA
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Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research
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Deep Learning Ensemble-Based Automated and High-Performing Recognition of Coffee Leaf Disease
inferred← citeshttps://doi.org/10.3390/ai6020021openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/cancers13040738openalex-snapshot
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inferred← citeshttps://doi.org/10.3390/cancers15154007openalex-snapshot
Deep Transfer Learning with Enhanced Feature Fusion for Detection of Abnormalities in X-ray Images
inferred← citeshttps://doi.org/10.3390/cells12020281openalex-snapshot
A Novel Nanosafety Approach Using Cell Painting, Metabolomics, and Lipidomics Captures the Cellular and Molecular Phenotypes Induced by the Unintentionally Formed Metal-Based (Nano)Particles
inferred← citeshttps://doi.org/10.3390/diagnostics12061359openalex-snapshot
Automatic Classification for Sagittal Craniofacial Patterns Based on Different Convolutional Neural Networks
inferred← citeshttps://doi.org/10.3390/diagnostics13101719openalex-snapshot
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Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks
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From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health
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Machine Learning Models for Abnormality Detection in Musculoskeletal Radiographs
inferred← citeshttps://doi.org/10.3390/s20164481openalex-snapshot
A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data
inferred← citeshttps://doi.org/10.3390/s22187007openalex-snapshot
Detection on Cell Cancer Using the Deep Transfer Learning and Histogram Based Image Focus Quality Assessment
inferred← citeshttps://doi.org/10.3390/s24113274openalex-snapshot
SensorNet: An Adaptive Attention Convolutional Neural Network for Sensor Feature Learning
inferred← citeshttps://doi.org/10.3390/w12010096openalex-snapshot
Convolutional Neural Network Coupled with a Transfer-Learning Approach for Time-Series Flood Predictions
inferred← citeshttps://doi.org/10.34133/2022/9861263openalex-snapshot
Deep Learning in Cell Image Analysis
inferred← citeshttps://doi.org/10.3934/math.2024156openalex-snapshot
A sophisticated Drowsiness Detection System via Deep Transfer Learning for real time scenarios
inferred← citeshttps://doi.org/10.3934/mbe.2021401openalex-snapshot
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inferred← citeshttps://doi.org/10.4018/978-1-7998-3095-5.ch001openalex-snapshot
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inferred← citeshttps://doi.org/10.46519/ij3dptdi.1029357openalex-snapshot
DISEASE DETECTION FROM CASSAVA LEAF IMAGES WITH DEEP LEARNING METHODS IN WEB ENVIRONMENT
inferred← citeshttps://doi.org/10.48550/arxiv.2111.11646openalex-snapshot
CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning
inferred← citeshttps://doi.org/10.48550/arxiv.2111.15519openalex-snapshot
Gram Barcodes for Histopathology Tissue Texture Retrieval
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Material Classification with a Transfer Learning based Deep Model on an imbalanced Dataset using an epochal Deming-Cycle-Methodology
inferred← citeshttps://doi.org/10.57709/18745124openalex-snapshot
Deep Functional Mapping For Predicting Cancer Outcome
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inferred← citeshttps://doi.org/10.64898/2026.04.23.720294openalex-snapshot
Semi supervised GAN for smart microscopy, fast and data efficient cell cycle classification
inferred← citeshttps://doi.org/10.70675/a58b9293zf458z47f1zb806za45d00711274openalex-snapshot
Developing a User-Friendly and Modular Framework for Deep Learning Methods in 3D Bioimage Segmentation
inferred← citeshttps://doi.org/10.70675/e30b336czb79bz4b87z8523z8b67d29d3815openalex-snapshot
Representation learning in Computational Pathology : Application to the Prediction of Molecular Cancer Features
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