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An efficient deep learning approach to detect neurodegenerative diseases using retinal images
(Brac University, 2023-01)
Neurodegenerative disorders are diagnosed through undergoing brain MRI, CT scans, genetic testing, and various laboratory screening tests which are often tedious, time consuming and beyond the means of most people’s financial ...
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 ...
A comparative analysis of the different CNN-LSTM model caption generation of medical images
(Brac University, 2023-05)
The intent of this paper is to make the process of interpreting and understanding
information within ultrasound pictures simpler and quicker by addressing the lack
of techniques for automatically deciphering medical ...
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 ...