An Efficient 1DCNN–LSTM Deep Learning Model for Assessment and Classification of fMRI-Based Autism Spectrum Disorder

Abdul Qayyum , M. Ahamed Khan , Abdesslam Benzinou (1, 2) , Moona Mazher , Manickam Ramasamy , Kalaiselvi Aramugam , C. Deisy , S. Sridevi , M. Suresh

1 ENIB - École Nationale d'Ingénieurs de Brest
2 Lab-STICC_OSE - Equipe Observations Signal & Environnement

Domaines: Informatique [cs]; Sciences de l'ingénieur [physics]

Abdul Qayyum, M. Ahamed Khan, Abdesslam Benzinou, Moona Mazher, Manickam Ramasamy, et al.. An Efficient 1DCNN–LSTM Deep Learning Model for Assessment and Classification of fMRI-Based Autism Spectrum Disorder. Innovative Data Communication Technologies and Application, 96, Springer Nature Singapore, pp.1039-1048, 2022, Lecture Notes on Data Engineering and Communications Technologies, ⟨10.1007/978-981-16-7167-8_77⟩. ⟨hal-03684541⟩