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Real-time fire detection based on feature analysis using enhanced color segmentation and novel foreground extraction
(Brac University, 2017-07)
This research proposes two effective real time fire detection techniques, based on video processing. The former technique is restricted to indoor conditions only while the later does not have such constraints. Both the ...
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 ...
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain
(Brac University, 2022-05)
Parkinson’s disease is a degenerative ailment caused by the loss of nerve cells in
the brain region known as the Substantia Nigra, which governs movement. These
nerve cells die or deteriorate, rendering them unable to ...
Automated fabric color prediction
(Brac University, 2023-05)
"This paper focuses on addressing some challenges faced by colorists and explores
various approaches to predict fabric color changes after dyeing processes. It empha-
sizes the importance of color prediction in the textile ...
Pyramid pooling enhanced ResUNet for accurate 3D brain image segmentation
(Brac University, 2023-09)
"Medical picture segmentation is important for clinical applications because it can
offer valuable information on disease identification. With the inclusion of deep
learning techniques, the original U-Net and ResUnet ...
Speech command classification based on deep neural networks
(Brac University, 2023-03)
In our day-to-day life there are lots of sounds that we are processing. To process
these sounds our brain absorb sound signals and provide us informative knowledge.
For human being this is not possible to extract every ...
Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
(Brac University, 2022-01)
Content centric network is a state-of-the-art networking architecture for content
distribution and content caching. However, it is inefficient to cache every content
in each network device. The modern edge computing ...
Analysing neural network models for detecting panic attacks with uncertainty analysis
(Brac University, 2024-01)
In our society and around the world a lot of people suffer from panic attacks. These
panic attacks can be mild or very intense physical stimulations that may incapacitate
an individual at the spot when the panic attack ...
Pneumonia Disease detection using the convolutional neural network
(Brac University, 2023-01)
A bacterial illness called pneumonia causes inflammation in the air passages with one
or even both lungs. The disease can range from mild to life-threatening. Diagnosing
the disease at an earlier stage is crucial for the ...
Enhanced hate speech detection in social media using transformer-based models
(Brac University, 2024-01)
Hate speech on social media can escalate into ”cyber conflict,” detrimentally impacting
social life. With the exponential growth of Internet users and media content,
identifying abusive language in audio and video content ...