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.

Xehetasun bibliografikoak
Egile Nagusiak: Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Beste egile batzuk: Alam, Md. Golam Rabiul
Formatua: Thesis
Hizkuntza:English
Argitaratua: Brac University 2022
Gaiak:
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
Sarrera elektronikoa:http://hdl.handle.net/10361/17333

Internet

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

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