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ICONS 2022: Knoxville, Tennessee, USA
- Thomas E. Potok, Catherine D. Schuman, Melika Payvand, Prasanna Date, Shruti R. Kulkarni, Yiran Chen, Robinson E. Pino, Brad Aimone, Mutsumi Kimura, Gregory Cohen, David Whittaker, Gordon Hirsch Wilson:
ICONS 2022: International Conference on Neuromorphic Systems, Knoxville, TN, USA, July 27 - 29, 2022. ACM 2022, ISBN 978-1-4503-9789-6 - Elvin Hajizada
, Patrick Berggold
Interactive continual learning for robots: a neuromorphic approach. 1:1-1:10 - Catherine D. Schuman
Evaluating Encoding and Decoding Approaches for Spiking Neuromorphic Systems. 2:1-2:9 - Akwasi Akwaboah, Ralph Etienne-Cummings:
LODeNNS: A Linearly-approximated and Optimized Dendrocentric Nearest Neighbor STDP. 3:1-3:8 - Mattias Nilsson
Spatiotemporal Pattern Recognition in Single Mixed-Signal VLSI Neurons with Heterogeneous Dynamic Synapses. 4:1-4:8 - Bojian Yin
Attentive Decision-making and Dynamic Resetting of Continual Running SRNNs for End-to-End Streaming Keyword Spotting. 5:1-5:8 - Yuan Zeng, Edward Jeffs, Terrence C. Stewart, Yevgeny Berdichevsky, Xiaochen Guo:
Optimizing Recurrent Spiking Neural Networks with Small Time Constants for Temporal Tasks. 6:1-6:8 - William Severa, J. Darby Smith
Learning to Parameterize a Stochastic Process Using Neuromorphic Data Generation. 7:1-7:7 - Riccardo Fontanini, David Esseni, Mirko Loghi:
Reducing the Spike Rate in Deep Spiking Neural Networks. 8:1-8:8 - Stein Stroobants
Design and implementation of a parsimonious neuromorphic PID for onboard altitude control for MAVs using neuromorphic processors. 9:1-9:7 - Terrence C. Stewart, Marc-Antoine Drouin, Michel Picard, Frank Billy Djupkep Dizeu, Antony Orth, Guillaume Gagné:
A Virtual Fence for Drones: Efficiently Detecting Propeller Blades with a DVXplorer Event Camera. 10:1-10:7 - Gavin Parpart
Dictionary Learning with Accumulator Neurons. 11:1-11:9 - Anand Sankaran, Paul Detterer, Kalpana Kannan, Nikolaos Alachiotis, Federico Corradi
An Event-driven Recurrent Spiking Neural Network Architecture for Efficient Inference on FPGA. 12:1-12:8 - Sidi Yaya Arnaud Yarga, Jean Rouat, Sean U. N. Wood:
Efficient Spike Encoding Algorithms for Neuromorphic Speech Recognition. 13:1-13:8 - Mahmoud Akl
Fine-tuning Deep Reinforcement Learning Policies with r-STDP for Domain Adaptation. 14:1-14:8 - Jonah Sengupta, Susan Liu, Andreas G. Andreou:
RetinoSim: an Event-based Data Synthesis Tool for Neuromorphic Vision Architecture Exploration. 15:1-15:9 - Prasanna Date, Thomas E. Potok, Catherine D. Schuman
Neuromorphic Computing is Turing-Complete. 16:1-16:10 - Tej Pandit, Dhireesha Kudithipudi:
Low-Shot Learning and Pattern Separation using Cellular Automata Integrated CNNs. 17:1-17:9 - Sonia M. Buckley, Adam N. McCaughan:
A general approach to fast online training of modern datasets on real neuromorphic systems without backpropagation. 18:1-18:8 - Kyle Henke, Michael A. Teti, Garrett T. Kenyon, Ben Migliori, Gerd J. Kunde:
Apples-to-spikes: The first detailed comparison of LASSO solutions generated by a spiking neuromorphic processor. 19:1-19:8 - Bodo Rueckauer, Marcel van Gerven:
Experiencing Prosthetic Vision with Event-Based Sensors. 20:1-20:7 - Steven C. Nesbit, Andrew O'Brien, Jocelyn Rego, Gavin Parpart
Think Fast: Time Control in Varying Paradigms of Spiking Neural Networks. 21:1-21:8 - James Ghawaly
A Neuromorphic Algorithm for Radiation Anomaly Detection. 22:1-22:6 - Julian Hille
Resonate-and-Fire Neurons for Radar Interference Detection. 23:1-23:4 - Charles Rizzo
Event-Based Camera Simulation Wrapper for Arcade Learning Environment. 24:1-24:5 - Felix Wang, Corinne Teeter, Sarah Luca, Srideep Musuvathy, James Bradley Aimone:
Distributed Localization with Grid-based Representations on Digital Elevation Models. 25:1-25:5 - Antony Orth, Terrence C. Stewart, Michel Picard, Marc-Antoine Drouin:
Towards a Laser Warning System in the Visible Spectrum using a Neuromorphic Camera. 26:1-26:4 - Alpha Renner
Sparse Vector Binding on Spiking Neuromorphic Hardware Using Synaptic Delays. 27:1-27:5 - Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman
Semi-Supervised Graph Structure Learning on Neuromorphic Computers. 28:1-28:4 - Madeleine Abernot, Thierry Gil, Aida Todri-Sanial
On-Chip Learning with a 15-neuron Digital Oscillatory Neural Network Implemented on ZYNQ Processor. 29:1-29:4 - Dominik Dold
Neuro-symbolic computing with spiking neural networks. 30:1-30:4
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