Classification of retinal diseases from OCT images using deep learning models

Classification of retinal diseases from OCT images using deep learning models

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografske podrobnosti
Main Authors:	Mokarrom, Md Saif, Shuvo, Md Anonto, Oyon, Nazmul Hasan, Munaja, Rifha Hossain, Roy, Soumik
Drugi avtorji:	Alam, Md. Ashraful
Format:	Thesis
Jezik:	English
Izdano:	Brac University 2024
Teme:	GradCAM Convolutional neural network Retina classification Machine learning > Medical applications Diagnostic imaging > Data processing Neural networks (Computer science) Deep learning (Machine learning)
Online dostop:	http://hdl.handle.net/10361/22885

Podobne knjige/članki

An interpretable diagnosis of retinal diseases using vision transformer and Grad-CAM
od: Bhuiyan, Mahdi Hasan, et al.
Izdano: (2024)

Deep Learning based Medicinal Plants Leaf Recognition
od: Mahalanabish, Tonusri
Izdano: (2023)

Deep learning-based waste classification system for efficient waste management
od: Nakib, Abdullah Al, et al.
Izdano: (2022)

An interpretable transformer based approach to classify Malaria from blood cell images
od: Islam, Mehafuza, et al.
Izdano: (2023)

A machine learning approach to detect DeepFake videos
od: Hassan, Md. Mahedi, et al.
Izdano: (2021)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
od: Sakir, Adnan, et al.
Izdano: (2023)

Learning a deep neural network for predicting phishing website
od: Das, Robat, et al.
Izdano: (2019)

Using deep learning algorithms to detect violent activities
od: Ammar, S.M. Rojin, et al.
Izdano: (2019)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
od: Mim, Ankhi Akter, et al.
Izdano: (2024)

Crop prediction based on geographical and climatic data using machine learning and deep learning
od: Alif, Al Amin, et al.
Izdano: (2019)

An efficient deep learning approach to classify white blood cells
od: Turja, Afif Ibna Kadir Khan, et al.
Izdano: (2024)

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
od: Ahmed, Istiak, et al.
Izdano: (2023)

Violent activity detection through surveillance camera using deep learning
od: Miah, Parvez, et al.
Izdano: (2023)

Visual object classification from fMRI data
od: Newaz, Syed Mishar, et al.
Izdano: (2022)

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
od: Datta, Nirjhor, et al.
Izdano: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
od: Ferdous, Md.Rubaiat, et al.
Izdano: (2024)

An analysis of word sense disambiguation in Bangla and English using supervised learning and a deep neural network classifier
od: Pasha, Maroof Ur Rahman
Izdano: (2016)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
od: Islam, Roman, et al.
Izdano: (2024)

Prediction of acute lymphoid leukemia using Privacy Preserving Neural Network
od: Khilji, Ishfaque Qamar, et al.
Izdano: (2021)

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
od: Bhuiyan, Abir Ahammed, et al.
Izdano: (2024)

Bang-lish sentiment classification using deep learning
od: Saleheen, Abrar, et al.
Izdano: (2023)

Corn leaf disease detection using deep convolution neural network
od: Rabbi, Rawhatur, et al.
Izdano: (2023)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
od: Sikder, Shihab Uddin, et al.
Izdano: (2022)

Classification of different magnetic structures from image data using deep neural networks
od: Ibn Hasib, Fahad, et al.
Izdano: (2023)

Cancer classification using deep learning from medical image data
od: Monir, Raiyan Janik, et al.
Izdano: (2022)

Crowd source based traffic analysis using machine learning algorithm
od: Orthy, Marzia Khan, et al.
Izdano: (2018)

An efficient ML approach to detect brain tumor using MRI images
od: Muktadir, MD. Arafat, et al.
Izdano: (2024)

Detection of skin cancer using Convolutional neural network
od: Ahsan, Abu Sa-adat Mohamed Moon-Im Al, et al.
Izdano: (2020)

Skin cancer classification for seven types of skin lesions
od: Rahman, Md. Tawsifur, et al.
Izdano: (2024)

An efficient deep learning approach to detect skin Cancer
od: Islam, Ashfaqul, et al.
Izdano: (2022)

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
od: Choudhury, Prionto Kumar, et al.
Izdano: (2024)

An interpretable deep learning approach to detect Alzheimer using MRI images
od: Oni, Farhan Anzum, et al.
Izdano: (2023)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
od: Haque, Samiha, et al.
Izdano: (2021)

Bangla text classification using machine learning and deep learning techniques
od: Salehin, Kamrus, et al.
Izdano: (2021)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
od: Ifty, Md. Hasin Sarwar, et al.
Izdano: (2024)

Prostate cancer detection using deep learning neural network with transfer learning approach
od: Badhon, Ariful Islam Mahmud, et al.
Izdano: (2022)

Explainable breast cancer detection from Histopathology images using transfer learning and XAI
od: Farabi, Farhan, et al.
Izdano: (2023)

Leveraging sequential deep learning models for detecting multitude of human action categories
od: Pranta, Kazi Al Refat, et al.
Izdano: (2024)

A machine learning approach to predict movie box-office success
od: Quader, Nahid, et al.
Izdano: (2018)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
od: Shahriar, Hasan, et al.
Izdano: (2022)