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An enhanced CNN model for classifying skin cancer
(Brac University, 2022-01)
Unrepaired deoxyribonucleic acid in skin cells causes skin cancer by generating genetic
abnormalities or mutations, rising day by day. Detecting and diagnosing skin
cancer in its early stages is expensive and challenging, ...
Deep neural network models for COVID-19 diagnosis from CT-Scan, explainability and analysis using trained models
(Brac University, 2021-10)
The world is going through a severe viral pandemic which is caused by COVID-
19. People infected with this virus, experience severe respiratory illness. The virus
spreads through particles of saliva or droplets from an ...
Detecting Deepfake images using deep convolutional neural network
(Brac University, 2021-09)
In recent years, advancement in the realm of machine learning has introduced a
feature known as Deepfake pictures, which allows users to substitute a genuine face
with a fake one that seems real. As a result, distinguishing ...
Music genre classification with convolutional neural network
(Brac University, 2022-01)
Today, Music is one of the effective forms of entertainment. Everyday new Music
is being composed, and the quantity of Music is increasing day by day. So, it is
essential to classify or categorize Music into different ...
Automated image caption generator in Bangla using multimodal learning
(Brac University, 2023-01)
Experiencing an image on-screen is a privilege that we often seem not to care about.
A visually impaired person does not have that luxury. A system that can automatically
produce closed captions of an image can thus help ...
Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
(Brac University, 2022-01)
Infectious and non-infectious respiratory diseases are among the major reasons for
deaths, financial and social crises around the world. However, medical personnel
still find it very difficult to detect the diseases using ...
An efficient deep learning approach for detecting Alzheimer’s disease using brain images
(Brac University, 2022-01)
Alzheimer’s disease (AD) is a disorder of the brain which causes the loss of memory.
This is a successively growing disease which means the severity of it will be upward
with the time. In this century, AD is one of the ...
Leveraging robust CNN architectures for real-time object recognition from conveyor belt
(Brac University, 2023-01)
In the innovative era, the problem of recognizing undesirable objects and individuals
on conveyor belts is addressed by various architectural or algorithmic approaches.
Conveyor belts are those by which things go in a ...
An efficient approach for binary classification in brain tumor detection using convolutional neural network
(Brac University, 2022-01)
Brain tumor detection using Convolutional Neural Network (CNN) models with
binary classification has significantly improved the reliability of medical imaging
through Deep Learning. The purpose of this research is to ...
Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
(Brac University, 2022-01)
Due to our unhealthy diets and the consumption of enhanced cholesterol in our
daily lives, our health has become vulnerable and at risk of different types of cardiac
diseases. The most common of them is Myocardial ...