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.

Bibliografiska uppgifter
Huvudupphovsmän:	Ahmed, Kazi sabab, Shariar, Khandaker Sadab, Naim, Naimul Hasan, Hazari, MD. Nayimur Rahman
Övriga upphovsmän:	Alam, Md. Golam Rabiul
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2022
Ämnen:	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
Länkar:	http://hdl.handle.net/10361/17333

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

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