Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Bibliografski detalji
Glavni autori:	Niaz, H.M, Tajrian, Nuha, Alam, Mohammad Ahsan Ibn, Limon, Md. Shahriar Khan, Saha, Sharnit
Daljnji autori:	Hossain, Muhammad Iqbal
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2024
Teme:	Diabetic Retinopathy (DR) Hybrid model Fusion model EfficientNetV2B3 EfficientNetV2S Inception-ResnetV2 MobileNetV2 Feature extraction KNN classifier APTOS-2019 DDR grading ExplainableAI LIME Artificial intelligence Neural networks (Computer science)
Online pristup:	http://hdl.handle.net/10361/22186

Similar Items

Comprehensive fingerprint recognition utilizing one shot learning with Siamese Network
od: Zaman, Sara Milham, i dr.
Izdano: (2023)

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

Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
od: Awwal, Alvina, i dr.
Izdano: (2021)

Skin disease detection and classification using deep learning
od: Shuvon, Mehedi Hasan, i dr.
Izdano: (2022)

Analyzing students’ concentration in online courses through Webcam
od: Asif, Md., i dr.
Izdano: (2024)

A comparative study of lung cancer prediction using deep learning
od: Mugdho, Aka Mohammad, i dr.
Izdano: (2023)

Plant disease diagnosis using deep transfer learning architectures- VGG19, MobileNetV2 and Inception-V3
od: Kobra, Khadija-Tul, i dr.
Izdano: (2022)

Simulation based distracted driver detection system using alcohol sensor and fusion of bioelectric signals to disseminate them through V2V/V2I to alleviate risky driving
od: Sikder, Md. Sarfaraj, i dr.
Izdano: (2019)

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

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

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

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

Automatic waste classification using deep learning and computer vision techniques
od: Akash, MD., i dr.
Izdano: (2023)

Detection of genetic diversity of SARS-CoV-2 in wastewater to monitor COVID-19 transmission
od: Sarwar, Subyeta Binte
Izdano: (2024)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
od: Haque, Abid Hossain, i dr.
Izdano: (2024)

Approaching transfer learning to identify correctly worn facial masks
od: Sadid, Tausif, i dr.
Izdano: (2021)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
od: Shahriar, Farhan, i dr.
Izdano: (2021)

A review paper on nanotheranostic insight into combatting impediments of the COVID-19 pandemic
od: Jamal, Tabassum Binte
Izdano: (2021)

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

An efficient face recognition model using multiple angular images and deep neural network architecture
od: Subah, Silma, i dr.
Izdano: (2024)

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

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

In-silico based vaccine development: targeting nucleocapsid protein of SARS-CoV-2.
od: Iva, Yesmine Akter
Izdano: (2022)

Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
od: Islam, Tahsin, i dr.
Izdano: (2021)

Overview of the risk factors, prevention and management of SARS-COV-2
od: Mustafa, Nashrah
Izdano: (2021)

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

FoodieCal: a convolutional neural network based food detection and calorie estimation system
od: Mashraf, Chowdhury Zerif, i dr.
Izdano: (2021)

Towards a socially just model: balancing hunger and response to the COVID-19 pandemic in Bangladesh
od: Rashid, Sabina Faiz, i dr.
Izdano: (2020)

An in silico Method to developing an epitope-based peptide vaccination against SARS-CoV-2's Envelope Protein (E)
od: Intesar, Mohammad Nafees
Izdano: (2023)

Combatting Covid-19 and the planned Reopening on 31 st May 2020 Take a ‘whole of the society approach’ - A statement from Bangladesh Health Watch (The Watch)
Izdano: (2020)

Follow-Up of practiced treatment regimens & health conditions of recovered patients of COVID-19 residing in Dhaka city: A survey-based descriptive cross-sectional study
od: Khan, Tahsin Shahrin
Izdano: (2021)

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

An efficient approach for recyclable waste detection and classification using image processing techniques
od: Chowdhury, Prabal Kumar, i dr.
Izdano: (2024)

Wave-wise comparison of COVID 19 based on SARS-CoV-2 Variants of Concern (VOCs) in Bangladesh, India, Sri Lanka, Pakistan, Nepal and the probable reasons behind the less devastating effects of Delta variant in Bangladesh: a review
od: Hasan, Mahfuzul, i dr.
Izdano: (2022)

A literature review on the efficacy of test kits for COVID-19
od: Sajid, Saiara Sajita
Izdano: (2022)

Covid-19 disease effects on pregnancy: a review
od: Ahmed, MD Tanvir
Izdano: (2024)

Use of vitamins in the treatment of covid-19
od: Ahmed, Tauhid
Izdano: (2021)

Determination of symptom association with COVID-19
od: Mahbub -E- Sobhanee, S.M.
Izdano: (2022)

A review on the pathophysiology and potential drugs for Covid-19
od: Modak, Srijani
Izdano: (2022)

A review on the use of minerals in the treatment of COVID-19
od: Billah, Chowdhury Showparna Parijat
Izdano: (2022)