Early detection of diabetic retinopathy using deep learning techniques

Early detection of diabetic retinopathy using deep learning techniques

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

Bibliographische Detailangaben
Hauptverfasser:	Gomes, Veronica Jessica, Alavee, Kazi Ahnaf, Sarda, Anirudh, Akhand, Zebel-E-Noor
Weitere Verfasser:	Mostakim, Moin
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2022
Schlagworte:	Data preprocessing Transfer learning Convolutional neural network Xception Inception Cognitive learning theory (Deep learning) Diabetic retinopathy Electronic data processing > Data preparation 286 906984 Engineering
Online Zugang:	http://hdl.handle.net/10361/15869

Ähnliche Einträge

Diabetic retinopathy detection and classification by using deep learning
von: Hossain, Shahriar, et al.
Veröffentlicht: (2022)

Diabetic retinopathy detection using machine learning
von: Maliha, Maisha, et al.
Veröffentlicht: (2018)

Diabetic retinopathy detection using image-processing
von: Zaman, Asif Uz, et al.
Veröffentlicht: (2016)

A novel and superior approach to diabetic management: utilization of a fuzzy-logic based system for precision insulin dosing in type 2 diabetes patients
von: Orni, Proma Roy
Veröffentlicht: (2018)

Detection of skin diseases using deep learning
von: Shodoy, Masuk Ur Rahman
Veröffentlicht: (2024)

Developing a machine learning based prognostic model and a supporting web-based application for predicting the possibility of early diabetes and diabetic kidney disease
von: Amin, M.M. Shahriar, et al.
Veröffentlicht: (2021)

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

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
von: Sakib, Hasibul, et al.
Veröffentlicht: (2024)

Visual object recognition using deep convolutional neural network
von: Ahmed, Sabbir
Veröffentlicht: (2017)

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
von: Niaz, H.M, et al.
Veröffentlicht: (2024)

Detection of fake identities on twitter using supervised machine learning
von: Rahman, MD. Takiur, et al.
Veröffentlicht: (2019)

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

An implementation and analysis of deep learning models for the detection of wheat diseases
von: Zubair, Ahmad, et al.
Veröffentlicht: (2024)

Predicting depression in Bangladeshi undergraduates using machine learning
von: Choudhury, Ahnaf Atef, et al.
Veröffentlicht: (2019)

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

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

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

Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
von: Datta, Pranab, et al.
Veröffentlicht: (2021)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
von: Raizan, Syed Ahsan, et al.
Veröffentlicht: (2021)

Document template identification and data extraction using machine learning and deep learning approach
von: Roy, Kaushik, et al.
Veröffentlicht: (2024)

Classifying insect pests from image data using deep learning
von: Mohsin, Md. Raiyan Bin, et al.
Veröffentlicht: (2022)

Pest detection system using machine learning techniques
von: Prithvi, Protyusha Barua, et al.
Veröffentlicht: (2022)

A machine learning-based approach for data analysis to ascertain suicidal individuals from Social media users
von: Nahar, Fatiha Binte Kamrun, et al.
Veröffentlicht: (2023)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
von: Shahriar, Hasan, et al.
Veröffentlicht: (2022)

Impact of machine learning and deep learning on biomedical applications and healthcare industry
von: Kabir, Md Saif, et al.
Veröffentlicht: (2024)

Comprehensive analysis and development of deep learning models for Bengali character’s spectrogram image classification in child speech: introduction of spectro SETNet
von: Ahmed, Syed Istiaque, et al.
Veröffentlicht: (2024)

Gender classification in Bangla language using deep learning-based voice analysis
von: Hakim, Talukder Juhaer, et al.
Veröffentlicht: (2024)

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

An autoencoder-based decentralized clustering leveraging model aggregation fusion strategy
von: Hasan, Nahid
Veröffentlicht: (2024)

An advanced data fabric architecture leveraging homomorphic encryption and federated learning
von: Rieyan, Sakib Anwar, et al.
Veröffentlicht: (2023)

Classification of peripheral blood cell images using deep learning
von: Aadi, Oyshik Ahmed, et al.
Veröffentlicht: (2024)

Deep convolutional GAN-based data augmentation for medical image classification
von: Datta, Joy, et al.
Veröffentlicht: (2022)

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
von: Tanvir, Farhan, et al.
Veröffentlicht: (2024)

Medical image reader powered by artificial intelligence
von: Palok, Tanvir Ahmed, et al.
Veröffentlicht: (2024)

Generation of realistic images from human drawn sketches using deep learning
von: Mahbub, Mohammed Julfikar Ali, et al.
Veröffentlicht: (2022)

A novel approach to forecast traffic congestion using CMTF and machine learning
von: Chowdhury, Md. Mohiuddin, et al.
Veröffentlicht: (2018)

Start up business solution using machine learning
von: Sohan, Saad Ahmed, et al.
Veröffentlicht: (2018)

Machine learning and statistics : the interface /
Veröffentlicht: (1997)

Verifying online signatures through an iterative device independent model
von: Tahsin, Samiha, et al.
Veröffentlicht: (2024)

A secured federated learning system leveraging confidence score to identify retinal disease
von: Eshan, M Sakib Osman, et al.
Veröffentlicht: (2023)