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A descriptive study on development of a transfer learning based fault detection model using 2D CNN for air compressors
(Brac University, 2021-06)
Fault Detection is essential for the safe and efficient operation of industrial manufacturing. Successful detection of fault features allows us to maintain a stableproduc- tion
line. Therefore, establishing a reliable and ...
Detection of multiple sclerosis using deep learning
(Brac University, 2021-01)
Accurate detection of white matter lesions in 3D Magnetic Resonance Images (MRIs) of patients with Multiple Sclerosis is essential for diagnosis and treatment evaluation of MS. It is strenuous for the optimal treatment of ...
Comparative analysis and implementation of credit risk prediction through distinct machine learning models
(Brac University, 2021-06)
Predicting the risk while lending money has always been a challenge for financial
institutions. To make such decisions many banks or financial organizations follow
different techniques to analyze a set of data. Manual ...
Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
(Brac University, 2021-09)
eep learning, a cutting-edge machine learning technique, has outperformed classical machine learning at detecting detailed structures in complex multi-dimensional
data, particularly in the field of computer vision. As ...
Recognition of Bangladeshi sign language from 2D videos using openpose and LSTM based RNN
(Brac University, 2021-02)
Sign-language recognition is an essential part of computer vision to solve a communication obstacle between the deaf-mute and the common. Bangladeshi Sign Language (BdSL) is the medium of communication of the deaf and dumb ...