Diabetic retinopathy detection and classification by using deep learning

Diabetic retinopathy detection and classification by using deep learning

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

Bibliografski detalji
Glavni autori:	Hossain, Shahriar, Evan, Md. Nurusshafi, Farhin, Fariya Zakir, Nabil, Mashrur Karim, Sadman, Sameen
Daljnji autori:	Chakrabarty, Amitabha
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2022
Teme:	Convolutional neural network Deep learning Diabetic retinopathy InceptionV3 Xception DenseNet-169 Cognitive learning theory (Deep learning) Neural networks (Computer science)
Online pristup:	http://hdl.handle.net/10361/16810

Similar Items

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

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

A deep learning approach towards soft biometrics attributes prediction using CNN
od: Kibria, Maharab, i dr.
Izdano: (2022)

Gender classification in Bangla language using deep learning-based voice analysis
od: Hakim, Talukder Juhaer, i dr.
Izdano: (2024)

Thoracic complication detection on chest X-rays using deep learning
od: Ratul, Rizwanul Hoque, i dr.
Izdano: (2021)

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

Classification of peripheral blood cell images using deep learning
od: Aadi, Oyshik Ahmed, i dr.
Izdano: (2024)

Visual object classification from fMRI data
od: Newaz, Syed Mishar, i dr.
Izdano: (2022)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
od: Khisa, Pushpakali, i dr.
Izdano: (2024)

Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
od: Promita, Samanta Tabassum, i dr.
Izdano: (2022)

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

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
od: Ismail, Sayem Mohammad, i dr.
Izdano: (2021)

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

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
od: Datta, Nirjhor, i dr.
Izdano: (2024)

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification
od: Bhuiyan, Abir Ahammed, i dr.
Izdano: (2024)

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

Skin disease detection and classification using deep learning
od: Shuvon, Mehedi 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 coronary artery blockage at an early stage using effective deep learning technique
od: Promit, Tahmid Ashrafee, i dr.
Izdano: (2023)

Pest detection system using machine learning techniques
od: Prithvi, Protyusha Barua, i dr.
Izdano: (2022)

Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
od: Reza, S. M. Mushfiq, i dr.
Izdano: (2024)

An efficient deep learning approach to detect skin Cancer
od: Islam, Ashfaqul, i dr.
Izdano: (2022)

Cancer classification using deep learning from medical image data
od: Monir, Raiyan Janik, i dr.
Izdano: (2022)

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

Predicting crime using deep learning
od: Shihab, Muhammad Nafees, i dr.
Izdano: (2024)

Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
od: Ashraf, S.M. Nabil, i dr.
Izdano: (2021)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
od: Sikder, Shihab Uddin, i dr.
Izdano: (2022)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
od: Ifty, Md. Hasin Sarwar, i dr.
Izdano: (2024)

Analysis of uncertainty in different neural network structures using monte carlo dropout
od: Islam, Md. Farhadul, i dr.
Izdano: (2024)

Enhancing Monkeypox diagnosis: a machine learning approach for skin lession classification
od: Nazmee, Namirah, i dr.
Izdano: (2024)

An efficient deep learning approach to detect skin cancer using image data
od: Chowdhury, Yaser Al Rahman, i dr.
Izdano: (2023)

Intracranial hemorrhage detection using CNN-LSTM fusion model
od: Ahmed, Kazi sabab, i dr.
Izdano: (2022)

A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
od: Chowdhury, Asif Hasan, i dr.
Izdano: (2023)

An efficient ML approach to detect brain tumor using MRI images
od: Muktadir, MD. Arafat, i dr.
Izdano: (2024)

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
od: Ahasan, Md. Mubtasim, i dr.
Izdano: (2022)

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

Analysis of uncertainty in different neural network structures using Monte Carlo Dropout
od: Islam, Md. Farhadul, i dr.
Izdano: (2024)

DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
od: Khan, Ibrahim
Izdano: (2023)

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

Visual object recognition using deep convolutional neural network
od: Ahmed, Sabbir
Izdano: (2017)