On the public citation graph

Parasitic Egg Detection and Classification: A Systematic Review

https://doi.org/10.2139/ssrn.4759366
0 signed · 52 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/978-981-13-9042-5_5openalex-extracted
Detection and Identification of Parasite Eggs from Microscopic Images of Fecal Samples
inferredcites →https://doi.org/10.1007/978-981-33-4084-8_29openalex-extracted
A Study on Classification Accuracy of Different Features in Identification of Parasite Eggs from Microscopic Images of Fecal Samples
inferredcites →https://doi.org/10.1007/s00436-015-4611-zopenalex-extracted
A robust and automatic method for human parasite egg recognition in microscopic images
inferredcites →https://doi.org/10.1007/s00521-022-06924-zopenalex-extracted
Automated diagnosis of schistosomiasis by using faster R-CNN for egg detection in microscopy images prepared by the Kato–Katz technique
inferredcites →https://doi.org/10.1007/s10462-007-9038-1openalex-extracted
Using active learning to annotate microscope images of parasite eggs
inferredcites →https://doi.org/10.1007/s10462-022-10209-1openalex-extracted
A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches
inferredcites →https://doi.org/10.1007/s11042-020-10191-2openalex-extracted
Enhanced SSD with interactive multi-scale attention features for object detection
inferredcites →https://doi.org/10.1007/s13534-013-0101-3openalex-extracted
Segmentation of human intestinal parasites from microscopy images using localized mean-separation based active contour model
inferredcites →https://doi.org/10.1007/s42600-023-00288-6openalex-extracted
Diagnostic support of parasitic infections with an AI-powered microscope
inferredcites →https://doi.org/10.1007/s42979-023-02406-8openalex-extracted
Parasitic Egg Detection and Classification in Low-Cost Microscopic Images Using Transfer Learning
inferredcites →https://doi.org/10.1016/j.biologicals.2009.02.008openalex-extracted
Neglected tropical disease vaccines
inferredcites →https://doi.org/10.1016/j.compbiomed.2014.05.012openalex-extracted
Cascaded-Automatic Segmentation for Schistosoma japonicum eggs in images of fecal samples
inferredcites →https://doi.org/10.1016/j.compbiomed.2020.103917openalex-extracted
Automated diagnosis of intestinal parasites: A new hybrid approach and its benefits
inferredcites →https://doi.org/10.1016/j.eswa.2007.07.020openalex-extracted
A robust technique based on invariant moments – ANFIS for recognition of human parasite eggs in microscopic images
inferredcites →https://doi.org/10.1016/j.eswa.2007.09.012openalex-extracted
An expert diagnosis system for classification of human parasite eggs based on multi-class SVM
inferredcites →https://doi.org/10.1016/j.ijsu.2010.02.007openalex-extracted
Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
inferredcites →https://doi.org/10.1016/j.imu.2018.10.007openalex-extracted
A neuro-fuzzy system for automated detection and classification of human intestinal parasites
inferredcites →https://doi.org/10.1016/j.imu.2019.100238openalex-extracted
Towards an automated medical diagnosis system for intestinal parasitosis
inferredcites →https://doi.org/10.1016/j.jmii.2021.07.014openalex-extracted
Helminth egg analysis platform (HEAP): An opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures
inferredcites →https://doi.org/10.1016/j.mex.2020.101158openalex-extracted
Helminth Egg Automatic Detector (HEAD): Improvements in development for digital identification and quantification of Helminth eggs and its application online
inferredcites →https://doi.org/10.1038/s41598-023-41711-3openalex-extracted
Parasitic egg recognition using convolution and attention network
inferredcites →https://doi.org/10.1093/her/cyh060openalex-extracted
Young people and healthy eating: a systematic review of research on barriers and facilitators
inferredcites →https://doi.org/10.1093/humupd/dmq004openalex-extracted
The patients' perspective on fertility care: a systematic review
inferredcites →https://doi.org/10.1109/10.923789openalex-extracted
Automatic identification of human helminth eggs on microscopic fecal specimens using digital image processing and an artificial neural network
inferredcites →https://doi.org/10.1109/acait53529.2021.9731120openalex-extracted
Recognition of parasite eggs in microscopic medical images based on YOLOv5
inferredcites →https://doi.org/10.1109/ecti-con49241.2020.9158084openalex-extracted
Automatic Detection and Characterization of Parasite Eggs using Deep Learning Methods
inferredcites →https://doi.org/10.1109/icecco.2013.6718223openalex-extracted
Microscopy image processing analaysis for automatic detection of human intestinal parasites ALO and TTO
inferredcites →https://doi.org/10.1109/icecte57896.2022.10114481openalex-extracted
Comparative Study of the Effect of Various Color Models on Classification of Parasitic Eggs
inferredcites →https://doi.org/10.1109/icip46576.2022.9897267openalex-extracted
ICIP 2022 Challenge on Parasitic Egg Detection and Classification in Microscopic Images: Dataset, Methods and Results
inferredcites →https://doi.org/10.1109/icip46576.2022.9897645openalex-extracted
Parasitic Egg Detection and Classification by Utilizing the YOLO Algorithm with Deep Latent Space Image Restoration and GrabCut Augmentation
inferredcites →https://doi.org/10.1109/icip46576.2022.9897844openalex-extracted
Localization and Classification of Parasitic Eggs in Microscpic Images Using An Efficientdet Detector
inferredcites →https://doi.org/10.1109/icip46576.2022.9897846openalex-extracted
Parasitic Egg Detection and Classification with Transformer-Based Architectures
inferredcites →https://doi.org/10.1109/icip46576.2022.9897858openalex-extracted
Parasitic Egg Detection with a Deep Learning Ensemble
inferredcites →https://doi.org/10.1109/iscaie.2012.6482095openalex-extracted
Human parasitic worm detection using image processing technique
inferredcites →https://doi.org/10.1109/tcyb.2022.3210294openalex-extracted
ExS-GAN: Synthesizing Anti-Forensics Images via Extra Supervised GAN
inferredcites →https://doi.org/10.1109/tmm.2021.3098422openalex-extracted
Anti-Forensics for Face Swapping Videos via Adversarial Training
inferredcites →https://doi.org/10.1109/tpami.2017.2781233openalex-extracted
HyperFace: A Deep Multi-Task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition
inferredcites →https://doi.org/10.1145/3310986.3311014openalex-extracted
Parasite worm egg automatic detection in microscopy stool image based on Faster R-CNN
inferredcites →https://doi.org/10.1155/2021/6648038openalex-extracted
Deep Learning Approach for Ascaris lumbricoides Parasite Egg Classification
inferredcites →https://doi.org/10.1186/1756-3305-7-37openalex-extracted
Global numbers of infection and disease burden of soil transmitted helminth infections in 2010
inferredcites →https://doi.org/10.1371/journal.pone.0175646openalex-extracted
Mathematical algorithm for the automatic recognition of intestinal parasites
inferredcites →https://doi.org/10.14569/ijacsa.2020.0111193openalex-extracted
Data Augmentation using Generative Adversarial Network for Gastrointestinal Parasite Microscopy Image Classification
inferredcites →https://doi.org/10.20965/jaciii.2023.p1113openalex-extracted
An Approach for Egg Parasite Classification Based on Ensemble Deep Learning
inferredcites →https://doi.org/10.32604/cmc.2018.02617openalex-extracted
Improved VGG Model for Road Traffic Sign Recognition
inferredcites →https://doi.org/10.32604/cmc.2020.08578openalex-extracted
An Efficient Image Analysis Framework for the Classification of Glioma Brain Images using CNN Approach
inferredcites →https://doi.org/10.3390/diagnostics13182978openalex-extracted
An Efficient and Effective Framework for Intestinal Parasite Egg Detection Using YOLOv5
inferredcites →https://doi.org/10.48550/arxiv.1608.02989openalex-extracted
Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics
inferredcites →https://doi.org/10.48550/arxiv.2203.02940openalex-extracted
Detection of Parasitic Eggs from Microscopy Images and the emergence of a new dataset
inferredcites →https://doi.org/10.5539/mas.v7n5p98openalex-extracted
Automated System for Diagnosis Intestinal Parasites by Computerized Image Analysis
inferredcites →https://doi.org/10.7326/0003-4819-72-4-601openalex-extracted
Diagnosis of Parasitic Infections
inferredcites →https://doi.org/10.7717/peerj-cs.1065openalex-extracted
Automatic recognition of parasitic products in stool examination using object detection approach
inferredcites →https://doi.org/10.13140/rg.2.2.35023.97449openalex-snapshot
Rethinking Object Detection in terms of Classification and Localization through Parallel Deep Learning Models
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.