These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
536 related articles for article (PubMed ID: 32408563)
21. A Scatter-and-Gather Spiking Convolutional Neural Network on a Reconfigurable Neuromorphic Hardware. Zou C; Cui X; Kuang Y; Liu K; Wang Y; Wang X; Huang R Front Neurosci; 2021; 15():694170. PubMed ID: 34867142 [TBL] [Abstract][Full Text] [Related]
22. Spiking neural networks for handwritten digit recognition-Supervised learning and network optimization. Kulkarni SR; Rajendran B Neural Netw; 2018 Jul; 103():118-127. PubMed ID: 29674234 [TBL] [Abstract][Full Text] [Related]
23. Spiking CMOS-NVM mixed-signal neuromorphic ConvNet with circuit- and training-optimized temporal subsampling. Dorzhigulov A; Saxena V Front Neurosci; 2023; 17():1177592. PubMed ID: 37534034 [TBL] [Abstract][Full Text] [Related]
24. MAP-SNN: Mapping spike activities with multiplicity, adaptability, and plasticity into bio-plausible spiking neural networks. Yu C; Du Y; Chen M; Wang A; Wang G; Li E Front Neurosci; 2022; 16():945037. PubMed ID: 36203801 [TBL] [Abstract][Full Text] [Related]
25. Towards biological plausibility of electronic noses: A spiking neural network based approach for tea odour classification. Sarkar ST; Bhondekar AP; Macaš M; Kumar R; Kaur R; Sharma A; Gulati A; Kumar A Neural Netw; 2015 Nov; 71():142-9. PubMed ID: 26356597 [TBL] [Abstract][Full Text] [Related]
26. Supervised learning in spiking neural networks: A review of algorithms and evaluations. Wang X; Lin X; Dang X Neural Netw; 2020 May; 125():258-280. PubMed ID: 32146356 [TBL] [Abstract][Full Text] [Related]
27. Odor Recognition with a Spiking Neural Network for Bioelectronic Nose. Li M; Ruan H; Qi Y; Guo T; Wang P; Pan G Sensors (Basel); 2019 Feb; 19(5):. PubMed ID: 30813574 [TBL] [Abstract][Full Text] [Related]
29. Demonstrating the Viability of Mapping Deep Learning Based EEG Decoders to Spiking Networks on Low-powered Neuromorphic Chips. Pals M; Belizon RJP; Berberich N; Ehrlich SK; Nassour J; Cheng G Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():6102-6105. PubMed ID: 34892509 [TBL] [Abstract][Full Text] [Related]
30. Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation. Liu Q; Pineda-García G; Stromatias E; Serrano-Gotarredona T; Furber SB Front Neurosci; 2016; 10():496. PubMed ID: 27853419 [TBL] [Abstract][Full Text] [Related]
31. A review of learning in biologically plausible spiking neural networks. Taherkhani A; Belatreche A; Li Y; Cosma G; Maguire LP; McGinnity TM Neural Netw; 2020 Feb; 122():253-272. PubMed ID: 31726331 [TBL] [Abstract][Full Text] [Related]
32. Supervised Learning in All FeFET-Based Spiking Neural Network: Opportunities and Challenges. Dutta S; Schafer C; Gomez J; Ni K; Joshi S; Datta S Front Neurosci; 2020; 14():634. PubMed ID: 32670012 [TBL] [Abstract][Full Text] [Related]
33. Heterogeneous Ensemble-Based Spike-Driven Few-Shot Online Learning. Yang S; Linares-Barranco B; Chen B Front Neurosci; 2022; 16():850932. PubMed ID: 35615277 [TBL] [Abstract][Full Text] [Related]
34. Experimental Demonstration of Supervised Learning in Spiking Neural Networks with Phase-Change Memory Synapses. Nandakumar SR; Boybat I; Le Gallo M; Eleftheriou E; Sebastian A; Rajendran B Sci Rep; 2020 May; 10(1):8080. PubMed ID: 32415108 [TBL] [Abstract][Full Text] [Related]
35. Multi-scale full spike pattern for semantic segmentation. Su Q; He W; Wei X; Xu B; Li G Neural Netw; 2024 Aug; 176():106330. PubMed ID: 38688068 [TBL] [Abstract][Full Text] [Related]
36. Going Deeper in Spiking Neural Networks: VGG and Residual Architectures. Sengupta A; Ye Y; Wang R; Liu C; Roy K Front Neurosci; 2019; 13():95. PubMed ID: 30899212 [TBL] [Abstract][Full Text] [Related]
37. Progressive Tandem Learning for Pattern Recognition With Deep Spiking Neural Networks. Wu J; Xu C; Han X; Zhou D; Zhang M; Li H; Tan KC IEEE Trans Pattern Anal Mach Intell; 2022 Nov; 44(11):7824-7840. PubMed ID: 34546918 [TBL] [Abstract][Full Text] [Related]
39. Application of Machine Learning for Fenceline Monitoring of Odor Classes and Concentrations at a Wastewater Treatment Plant. Cangialosi F; Bruno E; De Santis G Sensors (Basel); 2021 Jul; 21(14):. PubMed ID: 34300455 [TBL] [Abstract][Full Text] [Related]