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Now showing items 31-40 of 40
Intracranial hemorrhage detection using CNN-LSTM fusion model
(Brac University, 2022-05)
Intracranial Hemorrhage is a term used to describe bleeding between the brain tissue
and the skull or within the brain tissue itself. It is life-threatening and needs immediate
medical attention. As the first response, ...
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 ...
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, ...
BanglaBait: using transformers, neural networks & statistical classifiers to detect clickbaits in New Bangla Clickbait Dataset
(Brac University, 2022-01)
The art of luring us to click on certain content by exploiting our curiosity is recognized
as clickbait. Clickbait might be aggravating at times because it is misleading.
Several studies have worked on the detection of ...
Application of deep convolutional neural network in multiclass skin cancer classification using custom CNN architecture
(Brac University, 2023-05)
Skin diseases represent a significant global health concern, and prompt and pre-
cise diagnosis is necessary for efficient treatment. Convolutional Neural Networks
(CNNs), in particular, have shown tremendous promise in ...
An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
(Brac University, 2022-05)
Optical Coherence Tomography (OCT) is an effective approach for diagnosing retinal
problems that can be used in combination with traditional diagnostic testing
methods. We developed and implemented a deep Convolutional ...
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 ...
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 ...
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 ...
Silent voice: harnessing deep learning for lip-reading in Bangla
(Brac University, 2024-01)
Understanding speech just through lip movement is known as lipreading. It is a
crucial component of interpersonal interactions. The majority of the previous initiatives
attempted to address the English lipreading issue. ...