An efficient deep learning approach to detect retinal disease using optical coherence tomographic images

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images

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

Bibliografiske detaljer
Main Authors:	Khan, Farhan Sakib, Ferdaus, Nowshin, Hossain, Tamim, Islam, Quazi Sabrina, Islam, Md. Iftakharul
Andre forfattere:	Alam, Md. Ashraful
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2022
Fag:	Convolutional neural network Optical coherence tomography Deep learning Retinal Disease VGG16 VGG19 MobNetV2 ResNet50 DenseNet121 InceptionV3 InceptionResNetV2 Neural networks (Computer science)
Online adgang:	http://hdl.handle.net/10361/17570

Lignende værker

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
af: Rahman, Afridi Ibn, et al.
Udgivet: (2022)

Citrus leaf disease detection by image processing
af: Chowdhury, Mahir Faisal, et al.
Udgivet: (2024)

Analyzing students’ concentration in online courses through Webcam
af: Asif, Md., et al.
Udgivet: (2024)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
af: Ismail, Sayem Mohammad, et al.
Udgivet: (2021)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
af: Haque, Abid Hossain, et al.
Udgivet: (2024)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
af: Athina, Fahima Hasan, et al.
Udgivet: (2022)

Covid-19 infected lung detection using machine learning
af: Islam, Md. Muntaha, et al.
Udgivet: (2022)

A comparative study of lung cancer prediction using deep learning
af: Mugdho, Aka Mohammad, et al.
Udgivet: (2023)

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
af: Awwal, Alvina, et al.
Udgivet: (2021)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
af: Shahriar, Farhan, et al.
Udgivet: (2021)

A deep learning approach for pneumonia classiﬁcation from chest X-Ray images with ensemble modelling and explainable AI
af: Akhter, Nasrin
Udgivet: (2023)

Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
af: Datta, Pranab, et al.
Udgivet: (2021)

FoodieCal: a convolutional neural network based food detection and calorie estimation system
af: Mashraf, Chowdhury Zerif, et al.
Udgivet: (2021)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
af: Hossain, Mohammad Sakib, et al.
Udgivet: (2023)

A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
af: Chowdhury, Asif Hasan, et al.
Udgivet: (2023)

A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
af: Chowdhury, Asif Hasan, et al.
Udgivet: (2023)

An efficient face recognition model using multiple angular images and deep neural network architecture
af: Subah, Silma, et al.
Udgivet: (2024)

Approaching transfer learning to identify correctly worn facial masks
af: Sadid, Tausif, et al.
Udgivet: (2021)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
af: Irfanuddin, Chowdhury Mohammad, et al.
Udgivet: (2023)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
af: Khisa, Pushpakali, et al.
Udgivet: (2024)

Detection of coronary artery blockage at an early stage using effective deep learning technique
af: Promit, Tahmid Ashrafee, et al.
Udgivet: (2023)

Skin disease detection and classification using deep learning
af: Shuvon, Mehedi Hasan, et al.
Udgivet: (2022)

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

Identifying brain abnormalities using image processing and CNN models
af: Talukder, Ismat Shehrin, et al.
Udgivet: (2021)

Plant disease diagnosis using deep transfer learning architectures- VGG19, MobileNetV2 and Inception-V3
af: Kobra, Khadija-Tul, et al.
Udgivet: (2022)

Diabetic retinopathy detection and classification by using deep learning
af: Hossain, Shahriar, et al.
Udgivet: (2022)

An Efficient deep learning approach to detect Brain Tumor using MRI images
af: Islam, Annur Tasnim, et al.
Udgivet: (2022)

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

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
af: Niaz, H.M, et al.
Udgivet: (2024)

Tomato leaf disease detection using convolutional neural network
af: Hasan, Md. Riazul, et al.
Udgivet: (2023)

Bone age comparison using convolutional neural network
af: Nawaz, Fariha, et al.
Udgivet: (2019)

Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
af: Promita, Samanta Tabassum, et al.
Udgivet: (2022)

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

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

An efficient approach for recyclable waste detection and classification using image processing techniques
af: Chowdhury, Prabal Kumar, et al.
Udgivet: (2024)

Automatic waste classification using deep learning and computer vision techniques
af: Akash, MD., et al.
Udgivet: (2023)

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
af: Islam, Tahsin, et al.
Udgivet: (2021)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
af: Sarmi, Kaniz Fatima, et al.
Udgivet: (2022)

Obscure face recognition using deep neural networks
af: Akash, MD Shahadat Hossain, et al.
Udgivet: (2023)

Early detection of cervical cancer using deep neural networks
af: Akhund, Atoshi, et al.
Udgivet: (2023)