Efficient image processing and machine learning approach for predicting retinal diseases

Efficient image processing and machine learning approach for predicting retinal diseases

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Détails bibliographiques
Auteurs principaux:	Hasib, Mehadi Hasan, Sultana, Tasnim, Chowdhury, Chandrika
Autres auteurs:	Alam, Md. Ashraful
Format:	Thèse
Langue:	en_US
Publié:	Brac University 2021
Sujets:	Image Processing Deep Learning Neural Network Convolutional Neural Network Artificial Neural Network Retinal Disease
Accès en ligne:	http://dspace.bracu.ac.bd/xmlui/handle/10361/14451

Documents similaires

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

Pneumonia Disease detection using the convolutional neural network
par: Ashrafee, Md. Iftid, et autres
Publié: (2024)

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

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

An efficient deep learning approach to detect skin Cancer
par: Islam, Ashfaqul, et autres
Publié: (2022)

Visual object recognition using deep convolutional neural network
par: Ahmed, Sabbir
Publié: (2017)

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

An efficient deep learning approach for brain tumor detection using 3D convolutional neural network
par: Ali, Syed Muaz
Publié: (2023)

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
par: Tasawar, Ihtyaz Kader, et autres
Publié: (2021)

An efficient deep learning approach to classify white blood cells
par: Turja, Afif Ibna Kadir Khan, et autres
Publié: (2024)

An efficient ML approach to detect brain tumor using MRI images
par: Muktadir, MD. Arafat, et autres
Publié: (2024)

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

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
par: Ferdous, Md.Rubaiat, et autres
Publié: (2024)

A color vision approach based on the autoencoder technique and deep neural networks for reconstructing color images under various lighting conditions
par: Faisal, Asm, et autres
Publié: (2024)

Crime scene prediction by detecting threatening objects using convolutional neural network
par: Nakib, Mohammad, et autres
Publié: (2017)

Semantic text extraction from CAPTCHA using Neural Networking
par: Chowdhury, Iftekhar Kabir, et autres
Publié: (2022)

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

Single and multi-view 2D image processing for enhanced 3D object reconstruction
par: Ghosh, Swapnil, et autres
Publié: (2024)

Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
par: Mahbub, Riasat, et autres
Publié: (2022)

Comparison of deep transfer learning models for cancer diagnosis
par: Joya, Nadia Islam, et autres
Publié: (2023)

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

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

A color vision approach for reconstructing color images in different lighting conditions based on auto encoder technique using deep neural networks
par: Gomes, Paul Richie, et autres
Publié: (2021)

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

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
par: Sagor, Mostofa Kamal, et autres
Publié: (2021)

Incorporating deep features extracted from convolutional neural networks to utilize machine learning classifiers for improved identification of Maize Leaf Disease
par: Khan, Shama, et autres
Publié: (2024)

Image classification using deep neural network for efficient identification of traffic sign
par: Saha, Sourajit
Publié: (2018)

Early detection of parkinson’s disease using image processing and artificial neural network
par: Rumman, Mosarrat, et autres
Publié: (2018)

PlantGuard: intelligent plant disease detection
par: Khanom, Nazifa
Publié: (2024)

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

Leaf classification by feature extraction using CNN
par: Bhuiyan, Md. Mazharul Islam, et autres
Publié: (2020)

An efficient deep learning approach to detect skin cancer using image data
par: Chowdhury, Yaser Al Rahman, et autres
Publié: (2023)

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

Classification of different magnetic structures from image data using deep neural networks
par: Ibn Hasib, Fahad, et autres
Publié: (2023)

A comparative analysis of the different CNN-LSTM model caption generation of medical images
par: Amin, Mahzabin Yasmin Binte, et autres
Publié: (2023)

Detection of handwritten text using convolutional neural network
par: Jasim, Rabib Bin, et autres
Publié: (2024)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
par: Ishrak, Gazi Hasin, et autres
Publié: (2022)

Exploring deep features: deeper fully convolutional neural network for image segmentation
par: Kamran, Sharif Amit, et autres
Publié: (2017)

An Efficient deep learning approach to detect Brain Tumor using MRI images
par: Islam, Annur Tasnim, et autres
Publié: (2022)

A supervised machine learning approach to predict vulnerability to drug addiction
par: Faisal, Fahim, et autres
Publié: (2020)