Generative adversarial network and texture features applied to automatic glaucoma detection
@article{Bisneto2020GenerativeAN, title={Generative adversarial network and texture features applied to automatic glaucoma detection}, author={Tomaz Ribeiro Viana Bisneto and Ant{\^o}nio Os{\'e}as de Carvalho Filho and Deborah Maria Vieira Magalh{\~a}es}, journal={Appl. Soft Comput.}, year={2020}, volume={90}, pages={106165} }
18 Citations
Automated Classification of Glaucoma Using DWT and HOG Features with Extreme Learning Machine
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A new approach is suggested in this work to improve the accuracy of classification with fewer time characteristics and provides 96.5% accuracy for the overall database.
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- Computer Science2020 IEEE Symposium on Computers and Communications (ISCC)
- 2020
This paper presents a methodology for automatic classification of glaucoma using CapsNet, a recent model of deep learning that analyzes the hierarchical spatial relationships between characteristics to represent images, so that it requires fewer training samples than traditional CNNs to achieve efficient classification.
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- 2022
A novel classifier named fractional gravitational search-based hybrid deep neural network (FGSA-HDNN) is developed for the effective classification of glaucoma-infected images from the normal image and its accuracy rate is 98.75%.
A Review on Glaucoma Disease Detection Using Computerized Techniques
- Computer Science, MedicineIEEE Access
- 2021
This article aims to provide a comprehensive overview of various existing techniques that use machine learning to detect and diagnose glaucoma based on fundus images and will be able to identify gaps in current research.
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- Medicine, Computer ScienceClinical ophthalmology
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A systematic search of public databases was performed to identify relevant studies to overview the publicly available fundus image datasets used to train, validate, and test machine learning and deep learning methods for optic cup and disc segmentation.
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- Computer ScienceIEEE Access
- 2021
The most recent Deep Learning (DL) classifiers deliver accurate, fast, and reliable CSR detection, however, more research needs to be conducted on publicly available datasets to improve computation complexity for the reliable detection and diagnosis of CSR disease.
Glokom Hastalığının Evrişimli Sinir Ağı Mimarileri ile Tespiti
- Computer Science, MedicineDeu Muhendislik Fakultesi Fen ve Muhendislik
- 2021
The findings have proven that convolutional neural networks are a successful methods on classification of normal and glaucoma.
Cycle-consistent GAN-based stain translation of renal pathology images with glomerulus detection application
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- 2021
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