Browsing by Subject "CNN"
Now showing items 1-20 of 42
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Automatic brain tumor segmentation using U-ResUNet chain model approach
(Brac University, 2021-09)Identifying brain tumors precisely within the early stage is still a challenging problem for the medical sector consistent with recent research. In a previous research approved by Cancer. Net Editorial Board, it was ... -
Bengali hand sign language recognition using convolutional neural networks
(BRAC University, 2019-04)Throughout the world the number of deaf and mute population is rising ever so increasingly. In particular Bangladesh has around 2.6 million individuals who aren't able to communicate with society using spoken language. ... -
Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
(Brac University, 2020-04)Uterine cervical cancer is the second most regular gynecological harm around the world. The appraisal of the degree of sickness is fundamental for arranging ideal treatment. Imaging procedures are progressively utilized ... -
Child Safe Browser Extension: A Browser Extension to Detect Adultery and Violent Content to Make Safer Web for Children
(Brac University, 2021-05)The world is changing with the pace of information technology revolution and now a-days anybody can access to the internet including the children. Since birth These 21st century children are able to access to the di erent ... -
Classi fication of motor imagery tasks based on BCI paradigm
(Brac University, 2019-09)Motor imagery tasks are mental processes by which individual practices a set of actions in their mind without actually performing the physical movements. Research in the motor imagery tasks allow us to acquire critical ... -
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 ... -
Classification of damaged vegetation areas using convolutional neural network over satellite images
(Brac University, 2021-01)Forests and wild vegetation have always been highly significant natural resources throughout history and play a crucial role in keeping the climate and ecosystems well balanced. Over the years, there has been a growing ... -
A color vision approach considering weather conditions based on auto encoder techniques using deep neural networks
(Brac University, 2021-01)Color vision approach is a riveting field of technology crucial in pioneering innovations like autonomous vehicles, autonomous drone deliveries, automated stores, robots, infrastructure and surveillance monitoring programs ... -
A comparative study of deep learning methods for automating road condition characterization
(Brac University, 2020-04)Roads in Bangladesh provide infrastructural facilities to both agricultural as well as industrial sectors of the country. Distressed roads can cause fatal accidents as well as largely decelerate sector progress. This makes ... -
Comparison of different CNN architectures for brain tumor detection using fMRI
(Brac University, 2020-04)Brain is the most vital organ of human body which controls the entire nervous system of human body. In that case, if anything goes wrong inside our brain the entire nervous system gets collapsed. The brain tumors are the ... -
A convolutional neural network based model with improved activation function and optimizer for effective intrusion detection and classification
(Brac University, 2020-04)In today's world, technological advancements have entangled our nancial, social and many more other aspects of lives to the internet or some network. Moreover, with the development of IoT technologies, it has spread ... -
Critical retinal disease detection from optical coherence tomography images by deep convolutional neural network and explainable machine learning
(Brac University, 2021-01)Retinal disease diagnosis by machine learning can be achieved using Deep Neural Network based predictors. Use of Explainable Artificial Intelligence (XAI) has the potential to explain the black box of those neural network ... -
Data security model using deep learning and edge computing for Internet of Things (IoT) in smart city
(Brac University, 2021-09)In the current ongoing world of the IoT (Internet of Things) devices, it is absolutely vital to have a safe, secure and reliable cyberspace. A cyberspace or network where it is free from all sorts of unethical activities ... -
A deep face-mask detection model using DenseNet169 and image processing techniques
(Brac University, 2022-01)The world stood still during the massive breakout of the Covid-19 worldwide. This massive outbreak of this contagious disease was occurred by being airborne. Not only COVID but also there are many other contagious disease ... -
A deep learning approach towards soft biometrics attributes prediction using CNN
(Brac University, 2021-09)Any physical, behavioural or adhered human characteristics that we can observe from a person is known as Soft Biometric.The most common physical soft biometric attributes are height, age, ethnicity, facial hairs, gender, ... -
Deep learning-based waste classification system for efficient waste management
(Brac University, 2021-10)A smart waste management system plays a vital role in building cleanliness, hygienic, and healthier living for the inhabitants of a city. However, the inherent problems of the waste management system are still a matter ... -
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 brain tumor using deep neural networks from MRI images
(Brac University, 2021-06)A brain tumor is a collection of abnormal cells growth in brain. It is a neurological disease which causes great damage and affects other healthy cells of brain. It can be cancerous or non-cancerous. Nowadays, people are ... -
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 ... -
Detection of alzheimer's disease using deep learning
(Brac University, 2019-12)Machine Learning has been on top of its form over the last few years. It covers a vast area of predictive web browsing, email and text classification, object detection, face recognition etc. Among all of the other ...
