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.

Détails bibliographiques
Auteurs principaux: Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Autres auteurs: Alam, Md. Golam Rabiul
Format: Thèse
Langue:English
Publié: Brac University 2022
Sujets:
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
Accès en ligne:http://hdl.handle.net/10361/17333

Internet

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

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