Research graph
References from A calibrated multi-scale transformer-based dual deep convolutional neural network framework for robust parasitic egg recognition across diverse microscopy conditions. Local targets link to admitted publications; unresolved targets remain external evidence.
Diagnostic methods for detecting internal parasites of livestock
2020 · External reference
A review on diagnostic techniques in veterinary helminthlogy
2016 · External reference
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward
2022 · External reference
Advances in deep learning-based medical image analysis
10.34133/2021/8786793 · 2021 · External reference
Helminth egg analysis platform (HEAP): an opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures
10.1016/j.jmii.2021.07.014 · 2022 · External reference
New developments in diagnosis of intestinal parasites
2024 · External reference
Artificial intelligence-powered microscopy: Transforming the landscape of parasitology
2025 · External reference
Segmentation approaches of parasite eggs in microscopic images: A survey
10.1007/s42979-024-02709-4 · 2024 · External reference
Parasitic egg detection from microscopic images using convolutional neural networks
2023 · External reference
Advances towards automatic detection and classification of parasites microscopic images using deep convolutional neural network: methods, models and research directions
10.1007/s11831-022-09858-w · 2023 · External reference
An expert diagnosis system for classification of human parasite eggs based on multi-class SVM
10.1016/j.eswa.2007.09.012 · 2009 · External reference
Identification of eggs from different production systems based on hyperspectra and CS-SVM
10.1080/00071668.2017.1278625 · 2017 · External reference
Use of random forests and support vector machines to improve annual egg production estimation
10.1007/s12562-016-1033-5 · 2017 · External reference
Automated identification of monogeneans using digital image processing and K-nearest neighbour approaches
2016 · External reference
Discrimination of fish populations using parasites: Random forests on a ‘predictable’ host-parasite system
10.1017/s0031182010000739 · 2010 · External reference
Parasitic egg detection and classification in low-cost microscopic images using transfer learning
10.1007/s42979-023-02406-8 · 2023 · External reference
Deep learning approach for ascaris lumbricoides parasite egg classification
2021 · External reference
Detection and identification of parasite eggs from microscopic images of fecal samples
2020 · External reference
Development of a lab-on-a-disk platform with digital imaging for identification and counting of parasite eggs in human and animal stool
10.3390/mi10120852 · 2019 · External reference
A robust and automatic method for human parasite egg recognition in microscopic images
10.1007/s00436-015-4611-z · 2015 · External reference
DT4peis: detection transformers for parasitic egg instance segmentation
10.1007/s10489-024-06199-y · 2025 · External reference
Recognition of parasitic helminth eggs via a deep learning-based platform
10.3389/fmicb.2024.1485001 · 2024 · External reference
Parasitic egg recognition using convolution and attention network
10.1038/s41598-023-41711-3 · 2023 · External reference
ParaVisionNet: A multitask vision transformer framework for accurate detection and classification of parasitic eggs in microscopy images
10.1016/j.compeleceng.2026.110978 · 2026 · External reference
Advancements in medical image segmentation: A review of transformer models
10.1016/j.compeleceng.2025.110099 · 2025 · External reference
Comprehensive attention transformer for multi-label segmentation of medical images based on multi-scale feature fusion
10.1016/j.compeleceng.2025.110100 · 2025 · External reference
Unresolved reference
2018 · External reference
Automatic detection and characterization of parasite eggs using deep learning methods
2020 · External reference
On calibration of modern neural networks
2017 · External reference
A robust and automatic method for human parasite egg recognition in microscopic images
10.1007/s00436-015-4611-z · ExternalCitation · doi-reference
DT4peis: detection transformers for parasitic egg instance segmentation
10.1007/s10489-024-06199-y · ExternalCitation · doi-reference
Advances towards automatic detection and classification of parasites microscopic images using deep convolutional neural network: methods, models and research directions
10.1007/s11831-022-09858-w · ExternalCitation · doi-reference
Use of random forests and support vector machines to improve annual egg production estimation
10.1007/s12562-016-1033-5 · ExternalCitation · doi-reference
Parasitic egg detection and classification in low-cost microscopic images using transfer learning
10.1007/s42979-023-02406-8 · ExternalCitation · doi-reference
Segmentation approaches of parasite eggs in microscopic images: A survey
10.1007/s42979-024-02709-4 · ExternalCitation · doi-reference
Advancements in medical image segmentation: A review of transformer models
10.1016/j.compeleceng.2025.110099 · ExternalCitation · doi-reference
Comprehensive attention transformer for multi-label segmentation of medical images based on multi-scale feature fusion
10.1016/j.compeleceng.2025.110100 · ExternalCitation · doi-reference
ParaVisionNet: A multitask vision transformer framework for accurate detection and classification of parasitic eggs in microscopy images
10.1016/j.compeleceng.2026.110978 · ExternalCitation · doi-reference
An expert diagnosis system for classification of human parasite eggs based on multi-class SVM
10.1016/j.eswa.2007.09.012 · ExternalCitation · doi-reference
Helminth egg analysis platform (HEAP): an opened platform for microscopic helminth egg identification and quantification based on the integration of deep learning architectures
10.1016/j.jmii.2021.07.014 · ExternalCitation · doi-reference
Discrimination of fish populations using parasites: Random forests on a ‘predictable’ host-parasite system
10.1017/s0031182010000739 · ExternalCitation · doi-reference
Parasitic egg recognition using convolution and attention network
10.1038/s41598-023-41711-3 · ExternalCitation · doi-reference
Identification of eggs from different production systems based on hyperspectra and CS-SVM
10.1080/00071668.2017.1278625 · ExternalCitation · doi-reference
Recognition of parasitic helminth eggs via a deep learning-based platform
10.3389/fmicb.2024.1485001 · ExternalCitation · doi-reference
Development of a lab-on-a-disk platform with digital imaging for identification and counting of parasite eggs in human and animal stool
10.3390/mi10120852 · ExternalCitation · doi-reference
Advances in deep learning-based medical image analysis
10.34133/2021/8786793 · ExternalCitation · doi-reference
