Concept Learning in Neuromorphic Vision Systems: What Can We Learn from Insects?

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Journal of Software Engineering and Applications

ISSN Print: 1945-3116
ISSN Online: 1945-3124

Website: https://www.scirp.org/journal/jsea
E-mail: jsea@scirp.org

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Submission

"Concept Learning in Neuromorphic Vision Systems: What Can We Learn from Insects?"
written by Fredrik Sandin, Asad I. Khan, Adrian G. Dyer, Anang Hudaya M. Amin, Giacomo Indiveri, Elisabetta Chicca, Evgeny Osipov,
published by Journal of Software Engineering and Applications, Vol.7 No.5, 2014

has been cited by the following article(s):

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[1]	Area- and Energy-Efficient STDP Learning Algorithm for Spiking Neural Network SoC IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3041946

[2]	A Neuromorphic-Hardware Oriented Bio-Plausible Online-Learning Spiking Neural Network Model IEEE Access, 2019 DOI:10.1109/ACCESS.2019.2919163

[3]	A compact phenomenological digital neuron implementing the 20 Izhikevich behaviors 2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2017 DOI:10.1109/BIOCAS.2017.8325231

[4]	A fully-synthesized 20-gate digital spike-based synapse with embedded online learning 2017 IEEE International Symposium on Circuits and Systems (ISCAS), 2017 DOI:10.1109/ISCAS.2017.8050219

[5]	Estimation of Vectors Similarity by Their Randomized Binary Projections Cybernetics and Systems Analysis, 2015 DOI:10.1007/s10559-015-9774-1

[6]	Imitation of honey bees’ concept learning processes using Vector Symbolic Architectures Biologically Inspired Cognitive Architectures, 2015 DOI:10.1016/j.bica.2015.09.002

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