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Now showing items 21-30 of 34
An efficient deep learning approach to detect COVID-19 infected lungs using image data
(Brac University, 2022-01)
The beginning of 2020 will always be a dreadful chapter in human history. Even
with all the recent advancements in the medical sector, the COVID-19 virus proved
to be a major challenge for doctors all over the world. The ...
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, ...
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 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 ...
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 ...
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 ...
Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
(Brac University, 2024-01)
Adrenocortical Carcinoma (ACC) is a rare but highly lethal cancer that occurs
in the adrenal cortex. Accurate diagnosis of ACC are vital in order to determine
appropriate treatment strategies and predict patient outcomes. ...
Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
(Brac University, 2023-09)
Skin Cancer is a cancer form that has become very prevalent in recent times and, if
left untreated, has the potential to cause premature death. That is why early diagnosis
and treatment are important to cure this disease. ...
Deep learning based early Glaucoma detection
(Brac University, 2024-01)
Glaucoma is a severe eye condition that can lead to progressive vision impairment
if left untreated. Diagnosis and monitoring of glaucoma at an initial stage is critical
for effective treatment of the disease. However, ...