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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/15725
Title: Cogni-Net: Cognitive Feature Learning Through Deep Visual Perception
Authors: Mukherjee P.
Das A.
Bhunia A.K.
Pratim Roy, Partha
Published in: Proceedings of International Conference on Image Processing, ICIP
Abstract: Can we ask computers to recognize what we see from brain signals alone? Our paper seeks to utilize the knowledge learnt in the visual domain by popular pre-trained vision models and use it to teach a recurrent model being trained on brain signals to learn a discriminative manifold of the human brain's cognition of different visual object categories in response to perceived visual cues. For this we make use of brain EEG signals triggered from visual stimuli like images and leverage the natural synchronization between images and their corresponding brain signals to learn a novel representation of the cognitive feature space. The concept of knowledge distillation has been used here for training the deep cognition model, CogniNet1, by employing a student-teacher learning technique in order to bridge the process of inter-modal knowledge transfer. The proposed novel architecture obtains state-of-the-art results, significantly surpassing other existing models. The experiments performed by us also suggest that if visual stimuli information like brain EEG signals can be gathered on a large scale, then that would help to obtain a better understanding of the largely unexplored domain of human brain cognition. © 2019 IEEE.
Citation: Proceedings of International Conference on Image Processing, ICIP, (2019), 4539- 4543
URI: https://doi.org/10.1109/ICIP.2019.8803717
http://repository.iitr.ac.in/handle/123456789/15725
Issue Date: 2019
Publisher: IEEE Computer Society
Keywords: EEG Signal
Knowledge Transfer
Knowledge-distillation
Teacher-Student network
ISBN: 9.78154E+12
ISSN: 15224880
Author Scopus IDs: 57208923773
57211301249
57188719920
56880478500
Author Affiliations: Mukherjee, P., Institute of Engineering and Management, India
Das, A., Institute of Engineering and Management, India
Bhunia, A.K., Institute of Engineering and Management, India
Roy, P.P., Nanyang Technological University, Singapore
Corresponding Author: Bhunia, A.K.; Institute of Engineering and ManagementIndia; email: ayanbhunia@ntu.edu.sg
Appears in Collections:Conference Publications [CS]

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