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.

Bibliografiska uppgifter
Huvudupphovsmän:	Hasib, Mehadi Hasan, Sultana, Tasnim, Chowdhury, Chandrika
Övriga upphovsmän:	Alam, Md. Ashraful
Materialtyp:	Lärdomsprov
Språk:	en_US
Publicerad:	Brac University 2021
Ämnen:	Image Processing Deep Learning Neural Network Convolutional Neural Network Artificial Neural Network Retinal Disease
Länkar:	http://dspace.bracu.ac.bd/xmlui/handle/10361/14451

Liknande verk

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

Pneumonia Disease detection using the convolutional neural network
av: Ashrafee, Md. Iftid, et al.
Publicerad: (2024)

Classification of retinal diseases from OCT images using deep learning models
av: Mokarrom, Md Saif, et al.
Publicerad: (2024)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
av: Khan, Farhan Sakib, et al.
Publicerad: (2022)

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

Visual object recognition using deep convolutional neural network
av: Ahmed, Sabbir
Publicerad: (2017)

A deep learning approach for prediction of ADHD using brain structure
av: Siam, Shafin Ahad, et al.
Publicerad: (2024)

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

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
av: Tasawar, Ihtyaz Kader, et al.
Publicerad: (2021)

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

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

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

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

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

Crime scene prediction by detecting threatening objects using convolutional neural network
av: Nakib, Mohammad, et al.
Publicerad: (2017)

Semantic text extraction from CAPTCHA using Neural Networking
av: Chowdhury, Iftekhar Kabir, et al.
Publicerad: (2022)

Plant leaf disease identification
av: Hasan Mahin, Mohammad Rakibul, et al.
Publicerad: (2024)

Single and multi-view 2D image processing for enhanced 3D object reconstruction
av: Ghosh, Swapnil, et al.
Publicerad: (2024)

Design and evaluation of convolutional neural network for detection of Alzheimer’s disease using MRI data
av: Mahbub, Riasat, et al.
Publicerad: (2022)

Comparison of deep transfer learning models for cancer diagnosis
av: Joya, Nadia Islam, et al.
Publicerad: (2023)

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

A novel lightweight CNN approach for Bangladeshi sign language gesture recognition
av: Rahman, Aryan, et al.
Publicerad: (2023)

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

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

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

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

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

Early detection of parkinson’s disease using image processing and artificial neural network
av: Rumman, Mosarrat, et al.
Publicerad: (2018)

PlantGuard: intelligent plant disease detection
av: Khanom, Nazifa
Publicerad: (2024)

Deep learning based early Glaucoma detection
av: Islam, Aabrar, et al.
Publicerad: (2024)

Leaf classification by feature extraction using CNN
av: Bhuiyan, Md. Mazharul Islam, et al.
Publicerad: (2020)

An efficient deep learning approach to detect skin cancer using image data
av: Chowdhury, Yaser Al Rahman, et al.
Publicerad: (2023)

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

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

A comparative analysis of the different CNN-LSTM model caption generation of medical images
av: Amin, Mahzabin Yasmin Binte, et al.
Publicerad: (2023)

Detection of handwritten text using convolutional neural network
av: Jasim, Rabib Bin, et al.
Publicerad: (2024)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
av: Ishrak, Gazi Hasin, et al.
Publicerad: (2022)

Exploring deep features: deeper fully convolutional neural network for image segmentation
av: Kamran, Sharif Amit, et al.
Publicerad: (2017)

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

A supervised machine learning approach to predict vulnerability to drug addiction
av: Faisal, Fahim, et al.
Publicerad: (2020)