A Nonsynaptic Memory Based Neural Network for Hand-Written Digit Classification Using an Explainable Feature Extraction Method-Reference-Cited by-同舟云学术

A Nonsynaptic Memory Based Neural Network for Hand-Written Digit Classification Using an Explainable Feature Extraction Method

Published:2022-05-27 Issue: Volume: Page:
ISSN:
Container-title:2022 the 6th International Conference on Information System and Data Mining
language:
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Author:

Faghihi Faramarz¹,Cai Siqi¹,Moustafa Ahmed²,Alashwal Hany³

Affiliation:

1. Machine Listening Lab (MLL), University of Bremen, Germany

2. School of Psychology, Bond University, Australia and Department of Human Anatomy and Physiology, University of Johannesburg, South Africa

3. Department of Computer Science and Software Engineering, United Arab Emirates University, United Arab Emirates

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3546157.3546168

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4. Kadam, S., and Vaidya, V . ( 2018 ). “ Review and analysis of zero, one and few shot learning approaches ,” International Conference on Intelligent Systems Design and Applications, 100–112 . Kadam, S., and Vaidya, V. (2018). “Review and analysis of zero, one and few shot learning approaches,” International Conference on Intelligent Systems Design and Applications, 100–112.

5. (2020). Generalizing from a few examples: a survey on few-shot learning;J.;ACM Comput. Surveys.

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