RetinalNet-500: a newly developed CNN model for eye disease detection

RetinalNet-500: a newly developed CNN model for eye disease detection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2022.

Détails bibliographiques
Auteurs principaux:	Toki, Sadikul Alim, Rahman, Sohanoor, Fahim, SM Mohtasim Billah, Mostakim, Abdullah Al
Autres auteurs:	Rahman, Md. Khalilur
Format:	Thèse
Langue:	English
Publié:	Brac University 2023
Sujets:	Retinal diagnosis Fundus images CNN Deep learning ML Machine learning Cognitive learning theory
Accès en ligne:	http://hdl.handle.net/10361/18039

Documents similaires

Protovision: utilizing prototypical networks for retinal diseases classification based on few-shot learning
par: Nabil, Sheikh MD. Nafis Noor, et autres
Publié: (2024)

A secured federated learning system leveraging confidence score to identify retinal disease
par: Eshan, M Sakib Osman, et autres
Publié: (2023)

Deep learning based early Glaucoma detection
par: Islam, Aabrar, et autres
Publié: (2024)

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
par: Bhuiyan, Mahdi Hasan, et autres
Publié: (2024)

Efficient image processing and machine learning approach for predicting retinal diseases
par: Hasib, Mehadi Hasan, et autres
Publié: (2021)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
par: Irfanuddin, Chowdhury Mohammad, et autres
Publié: (2023)

Character animation using reinforcement learning and imitation learning algorithms
par: Tahmid, Tokey, et autres
Publié: (2021)

Identifying brain abnormalities using image processing and CNN models
par: Talukder, Ismat Shehrin, et autres
Publié: (2021)

A comparative analysis of deep learning and hybrid models to diagnose multi-class skin cancer
par: Nawrin, Ishrat Nur, et autres
Publié: (2023)

Application of CNN based architectures in detection of distracted drivers
par: Arafin, Irfana, et autres
Publié: (2023)

Explainable artificial intelligence and model calibration for water quality prediction
par: Hellen, Nakayiza
Publié: (2022)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
par: Hasan, M. M. Kamrul, et autres
Publié: (2022)

Statistical analysis of network data flows and predictions using statistical and machine learning regression models
par: Boateng, Albert, et autres
Publié: (2024)

Early detection of breast cancer using machine learning
par: Fuad, Wasi Mohammad
Publié: (2019)

Classification of retinal diseases from OCT images using deep learning models
par: Mokarrom, Md Saif, et autres
Publié: (2024)

Intracranial hemorrhage detection using CNN-LSTM fusion model
par: Ahmed, Kazi sabab, et autres
Publié: (2022)

Mobile sensors based human activity recognition using machine learning with explainable ML
par: Rahman, Raihan, et autres
Publié: (2021)

Occluded object detection for autonomous vehicles employing YOLOv5, YOLOX and Faster R-CNN
par: Mostafa, Tanzim, et autres
Publié: (2022)

In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
par: Haque, Hossain MD. Hasibul, et autres
Publié: (2024)

A deep learning approach towards soft biometrics attributes prediction using CNN
par: Kibria, Maharab, et autres
Publié: (2022)

A deep learning approach for prediction of ADHD using brain structure
par: Siam, Shafin Ahad, et autres
Publié: (2024)

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
par: Fiona, Driciru, et autres
Publié: (2024)

Quantum lattice learning and explainable artificial intelligence for maternal and child healthcare
par: Marvin, Ggaliwango
Publié: (2022)

How we learn and why we don't : student survival guide using the cognitive profile inventory /
par: Krause, Lois Breur
Publié: (2008)

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
par: Bhuiyan, Abir Ahammed, et autres
Publié: (2024)

Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
par: Reza, S. M. Mushfiq, et autres
Publié: (2024)

Plant leaf disease identification
par: Hasan Mahin, Mohammad Rakibul, et autres
Publié: (2024)

Development of mobile learning system based on android app
par: Samrin, Sama, et autres
Publié: (2018)

Comparative analysis and machine learning predictions of cervical cancer incidence: a multi-national study
par: Faisal, Shah
Publié: (2024)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
par: Khan, Farhan Sakib, et autres
Publié: (2022)

A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
par: Rahman, Aryan, et autres
Publié: (2023)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
par: Toufique, S.M, et autres
Publié: (2024)

Micro-learning modules are linked to enhanced retention of the learners and can be geared toward subconscious knowledge acquisition in an organization
par: Siddique, Noman
Publié: (2024)

Learning theories in childhood /
par: Gray, Colette, et autres
Publié: (2015)

Machine fault diagnosis using a modified transferable CNN
par: Shammi, Sanjana Khan
Publié: (2024)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
par: Radiah, Faiza, et autres
Publié: (2024)

An interpretable transformer based approach to classify Malaria from blood cell images
par: Islam, Mehafuza, et autres
Publié: (2023)

Development of learning process perceived by the students of the pharmacy department of different universities in Bangladesh
par: Rahman, Sharjana
Publié: (2019)

Essentials of learning : the new cognitive learning for students of education /
par: Travers, Robert Morris William, 1913-

Analysis of the impact of online education using EEG signals and machine learning algorithms
par: Hoque, Ehsanul, et autres
Publié: (2021)