Deep learning-based CNN for multiclassification of ocular diseases using transfer learning
Effective and timely diagnosis and treatment of ocular diseases is essential for swift recovery
of the patients. Among ocular diseases, cataract and glaucoma are the most prevalent …
of the patients. Among ocular diseases, cataract and glaucoma are the most prevalent …
Classification of eye diseases using hybrid CNN-RNN models
M Londhe - 2021 - norma.ncirl.ie
Early diagnosis of eye diseases is essential to prevent irreversible vision loss. The
traditional method used by ophthalmologists is to manually screen, images captured of back …
traditional method used by ophthalmologists is to manually screen, images captured of back …
Detection of cataract, diabetic retinopathy and glaucoma eye diseases with deep learning approach
G ARSLAN, ÇB Erdaş - Intelligent Methods In Engineering Sciences, 2023 - imiens.org
Eye diseases are one of the serious health problems affecting human life. Cataract, diabetic
retinopathy and glaucoma eye diseases cause visual impairment and cause irreversible eye …
retinopathy and glaucoma eye diseases cause visual impairment and cause irreversible eye …
Deep Learning-Based Classification of Ocular Diseases Using Convolutional Neural Networks
Ocular diseases can range from mild discomfort to severe vision loss or even blindness, and
can affect people of all ages. Early detection and treatment are crucial to prevent or delay …
can affect people of all ages. Early detection and treatment are crucial to prevent or delay …
Deep transfer learning approaches to predict glaucoma, cataract, choroidal neovascularization, diabetic macular edema, drusen and healthy eyes: an experimental …
Artificial intelligence (AI) has lately witnessed an age of tremendous expansion across
several industries, including healthcare. In recent years, substantial advancements in AI …
several industries, including healthcare. In recent years, substantial advancements in AI …
[PDF][PDF] Multiclass Classification and Identification of the External Eye Diseases using Deep CNN
F Rashid, J Abate, A Abdi - Indian Journal …, 2024 - sciresol.s3.us-east-2.amazonaws …
Objective: These eye illnesses can be either internal eye diseases or external eye diseases.
The purpose of research is to find the right model for better performance to identify the …
The purpose of research is to find the right model for better performance to identify the …
EyeCNN: exploring the potential of convolutional neural networks for identification of multiple eye diseases through retinal imagery
Background The eyes are the most important part of the human body as these are directly
connected to the brain and help us perceive the imagery in daily life whereas, eye diseases …
connected to the brain and help us perceive the imagery in daily life whereas, eye diseases …
Glaucoma detection using image processing and supervised learning for classification
S Joshi, B Partibane, WA Hatamleh… - Journal of …, 2022 - Wiley Online Library
A difficult challenge in the realm of biomedical engineering is the detection of physiological
changes occurring inside the human body, which is a difficult undertaking. At the moment …
changes occurring inside the human body, which is a difficult undertaking. At the moment …
Ocular disease detection using advanced neural network based classification algorithms
NM Dipu, SA Shohan, KMA Salam - Asian Journal For Convergence In …, 2021 - asianssr.org
One of the most challenging tasks for ophthalmologists is early screening and diagnosis of
ocular diseases from fundus images. However, manual diagnosis of ocular diseases is …
ocular diseases from fundus images. However, manual diagnosis of ocular diseases is …
Automatic eye disease detection using machine learning and deep learning models
N Badah, A Algefes, A AlArjani, R Mokni - Pervasive Computing and …, 2022 - Springer
Glaucoma is a serious eye disease that affects a lot of people around the world. Deep
learning architectures have been widely used in recent years for image recognition tasks. In …
learning architectures have been widely used in recent years for image recognition tasks. In …