Intracranial hemorrhage detection using CNN-LSTM fusion model

Intracranial hemorrhage detection using CNN-LSTM fusion model

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Άλλοι συγγραφείς: Alam, Md. Golam Rabiul
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2022
Θέματα:
Deep learning
Convolutional neural network (CNN)
Magnetic Resonance Imaging (MRI)
Magnetic Resonance Angiogram (MRA)
Intracranial hemorrhage
Recurrent Neural Network (RNN)
Cognitive learning theory (Deep learning)
Neural networks (Computer science)
Machine learning
Διαθέσιμο Online:http://hdl.handle.net/10361/17333

Διαδίκτυο

http://hdl.handle.net/10361/17333

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