A squeeze and excitation ResNeXt-based deep learning model for Bangla handwritten basic to compound character recognition

A squeeze and excitation ResNeXt-based deep learning model for Bangla handwritten basic to compound character recognition

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2021.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Khan, Mohammad Meraj
Άλλοι συγγραφείς: Rahman, Md. Khalilur
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2022
Θέματα:
Bangla handwritten-character recognition
Deep convolutional neural network
Squeeze and excitation ResNext
Optical character recognition
Global average pooling
Character recognition
Artificial intelligence.
Simulation.
Neural networks (Computer science)
Cognitive learning theory (Deep learning)
Διαθέσιμο Online:http://hdl.handle.net/10361/16368

Διαδίκτυο

http://hdl.handle.net/10361/16368

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