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.

Bibliografski detalji
Glavni autori: Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Daljnji autori: Alam, Md. Golam Rabiul
Format: Disertacija
Jezik:English
Izdano: Brac University 2022
Teme:
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
Online pristup:http://hdl.handle.net/10361/17333

Internet

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

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