Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning

Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Opis bibliograficzny
Główni autorzy:	Datta, Pranab, Islam, Saniul, Das, Retuparna, Zabir, Mihiran Uddin
Kolejni autorzy:	Alam, Md. Golam Rabiul
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2021
Hasła przedmiotowe:	Machine Learning Image classification Artificial Intelligence Optical Coherence Tomography CNN Inception V3 Resnet50 VGG16 Xception Black Box LRP
Dostęp online:	http://hdl.handle.net/10361/15762

Podobne zapisy

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
od: Khan, Farhan Sakib, i wsp.
Wydane: (2022)

Retinal Diseases Detection using Deep Learning
od: Mashfi, Shahriar, i wsp.
Wydane: (2023)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
od: Shahriar, Hasan, i wsp.
Wydane: (2022)

An efficient deep learning approach to detect neurodegenerative diseases using retinal images
od: Irfanuddin, Chowdhury Mohammad, i wsp.
Wydane: (2023)

Diabetic retinopathy detection using machine learning
od: Maliha, Maisha, i wsp.
Wydane: (2018)

Classiﬁcation of damaged vegetation areas using convolutional neural network over satellite images
od: Haque, Samiha, i wsp.
Wydane: (2021)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
od: Rahman, Afridi Ibn, i wsp.
Wydane: (2022)

A deep learning approach to depression detection based on Convolutional Neural Networks and Transfer Learning
od: Sarmi, Kaniz Fatima, i wsp.
Wydane: (2022)

Brain tumor detection with convolutional neural network
od: Galib, Abrar Tahmid, i wsp.
Wydane: (2024)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
od: Hossain, Mohammad Sakib, i wsp.
Wydane: (2023)

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

Corn leaf disease detection using deep convolution neural network
od: Rabbi, Rawhatur, i wsp.
Wydane: (2023)

Implementing temporally coherent clustering on student activity to predict exam performance & optimizing the learning pathway through markov chain analysis
od: Anough, Ahmed Saquif Alam, i wsp.
Wydane: (2019)

Multi-classification Network for Detecting Skin Diseases using Deep Learning and XAI
od: Athina, Fahima Hasan, i wsp.
Wydane: (2022)

RetinalNet-500: a newly developed CNN model for eye disease detection
od: Toki, Sadikul Alim, i wsp.
Wydane: (2023)

Heart disease prediction using machine learning algorithms
od: Ali, Musfiq, i wsp.
Wydane: (2019)

Classification of retinal diseases from OCT images using deep learning models
od: Mokarrom, Md Saif, i wsp.
Wydane: (2024)

Tomato leaf disease detection using convolutional neural network
od: Hasan, Md. Riazul, i wsp.
Wydane: (2023)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
od: Sakir, Adnan, i wsp.
Wydane: (2023)

Public vehicle ETA system using machine learning
od: Kabir, Md. Miraz, i wsp.
Wydane: (2018)

Predicting depression in Bangladeshi undergraduates using machine learning
od: Choudhury, Ahnaf Atef, i wsp.
Wydane: (2019)

Analysis of the impact of online education using EEG signals and machine learning algorithms
od: Hoque, Ehsanul, i wsp.
Wydane: (2021)

Demystifying black-box learning models of rumor detection from social media posts
od: Tafannum, Faiza, i wsp.
Wydane: (2021)

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

Deep convolutional GAN-based data augmentation for medical image classification
od: Datta, Joy, i wsp.
Wydane: (2022)

Citrus leaf disease detection by image processing
od: Chowdhury, Mahir Faisal, i wsp.
Wydane: (2024)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
od: Toufique, S.M, i wsp.
Wydane: (2024)

Alumni opportunities using machine learning
od: Siaum, Arshif Sharlimin, i wsp.
Wydane: (2019)

Machine learning as an indicator for breast cancer prediction
od: Shadman, Tahsin Mohammed, i wsp.
Wydane: (2019)

Diabetic retinopathy detection and classification by using deep learning
od: Hossain, Shahriar, i wsp.
Wydane: (2022)

A secured federated learning system leveraging confidence score to identify retinal disease
od: Eshan, M Sakib Osman, i wsp.
Wydane: (2023)

Explainable Deepfake video detection using Convolutional Neural Network and CapsuleNet
od: Ishrak, Gazi Hasin, i wsp.
Wydane: (2022)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
od: Shawan, Naveed Rahman, i wsp.
Wydane: (2019)

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

Observing mega cities to grow from space and predicting its growth using machine learning techniques
od: Chakma, Mitesh, i wsp.
Wydane: (2018)

Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
od: Alhossen, Md., i wsp.
Wydane: (2021)

Pattern recognition with Quantum Support Vector Machine(QSVM) on near term quantum processors.
od: Ahmed, Sajjad
Wydane: (2019)

Early detection of diabetic retinopathy using deep learning techniques
od: Gomes, Veronica Jessica, i wsp.
Wydane: (2022)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
od: Ferdous, Md.Rubaiat, i wsp.
Wydane: (2024)

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
od: Fahim, Kaji Mehedi Hasan, i wsp.
Wydane: (2024)