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ORCIDICONS 2021: Knoxville, Tennessee, USA
- Thomas E. Potok, Melika Payvand, Catherine D. Schuman, Prasanna Date, Mutsumi Kimura, Cory E. Merkel, Brad Aimone, Sonia M. Buckley, Yiran Chen, Gregory Cohen, Todd Hylton, Robert M. Patton, Robinson E. Pino, Garrett S. Rose:
ICONS 2021: International Conference on Neuromorphic Systems 2021, Knoxville, TN, USA, July 27-29, 2021. ACM 2021, ISBN 978-1-4503-8691-3 - Chen Li, Steve B. Furber:
Towards Biologically-Plausible Neuron Models and Firing Rates in High-Performance Deep Spiking Neural Networks. 1:1-1:7 - Richard Boone, Wenrui Zhang
, Peng Li:
Efficient Biologically-Plausible Training of Spiking Neural Networks with Precise Timing. 2:1-2:8 - Nicholas Alonso, Emre Neftci:
Tightening the Biological Constraints on Gradient-Based Predictive Coding. 3:1-3:9 - J. Parker Mitchell, Catherine D. Schuman:
Low Power Hardware-In-The-Loop Neuromorphic Training Accelerator. 4:1-4:4 - Mahyar Shahsavari, David B. Thomas, Andrew D. Brown, Wayne Luk:
Neuromorphic Design Using Reward-based STDP Learning on Event-Based Reconfigurable Cluster Architecture. 5:1-5:8 - Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation. 6:1-6:7 - Yuan Zeng, Terrence C. Stewart, Zubayer Ibne Ferdous, Yevgeny Berdichevsky, Xiaochen Guo:
Temporal Learning with Biologically Fitted SNN Models. 7:1-7:8 - Prasanna Date, Bill Kay, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok:
Computational Complexity of Neuromorphic Algorithms. 8:1-8:7 - Zixuan Zhao, Nathan Wycoff, Neil Getty, Rick Stevens, Fangfang Xia:
Neko: a Library for Exploring Neuromorphic Learning Rules. 9:1-9:5 - Adarsha Balaji, Shihao Song, Twisha Titirsha, Anup Das, Jeffrey L. Krichmar, Nikil D. Dutt, James A. Shackleford, Nagarajan Kandasamy, Francky Catthoor:
NeuroXplorer 1.0: An Extensible Framework for Architectural Exploration with Spiking Neural Networks. 10:1-10:9 - Thao N. N. Nguyen, Bharadwaj Veeravalli, Xuanyao Fong:
Connection Pruning for Deep Spiking Neural Networks with On-Chip Learning. 11:1-11:8 - Hin Wai Lui, Emre Neftci:
Hessian Aware Quantization of Spiking Neural Networks. 12:1-12:5 - Mahmoud Akl, Yulia Sandamirskaya, Florian Walter, Alois C. Knoll:
Porting Deep Spiking Q-Networks to neuromorphic chip Loihi. 13:1-13:7 - Maryam Parsa, Catherine D. Schuman, Nitin Rathi, Amirkoushyar Ziabari, Derek C. Rose, J. Parker Mitchell, J. Travis Johnston, Bill Kay, Steven R. Young, Kaushik Roy:
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. 14:1-14:8 - Wilkie Olin-Ammentorp, Maxim Bazhenov:
Bridge Networks: Relating Inputs through Vector-Symbolic Manipulations. 15:1-15:6 - Ruomin Zhu, Alon Loeffler, Joel Hochstetter, Adrian Diaz-Alvarez, Tomonobu Nakayama, Adam Z. Stieg, James K. Gimzewski, Joseph T. Lizier, Zdenka Kuncic:
MNIST classification using Neuromorphic Nanowire Networks. 16:1-16:4 - Heidi Komkov, Liam Pocher, Alessandro Restelli, Brian Hunt, Daniel P. Lathrop:
Reservoir Computing Using Networks of CMOS Logic Gates. 17:1-17:7 - Alexander Jones, Krishnamurthy Vemuru:
The Need for Scalable Digital Spiking Neurons. 18:1-18:4 - Idir Mellal, David Crompton, Milos R. Popovic, Milad Lankarany:
A Flexible FPGA Implementation of Morris-Lecar Neuron for Reproducing Different Neuronal Behaviors. 19:1-19:5 - Weng Fei Low, Ankit Sonthalia, Zhi Gao, André van Schaik, Bharath Ramesh:
Superevents: Towards Native Semantic Segmentation for Event-based Cameras. 20:1-20:8 - Alejandro Linares-Barranco, Antonio Rios-Navarro, Salvador Canas-Moreno, Enrique Piñero-Fuentes, Ricardo Tapiador-Morales, Tobi Delbrück:
Dynamic Vision Sensor integration on FPGA-based CNN accelerators for high-speed visual classification. 21:1-21:7 - James S. Plank, Chaohui Zheng, Catherine D. Schuman, Christopher Dean:
Spiking Neuromorphic Networks for Binary Tasks. 22:1-22:9 - Robert M. Patton, Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Nicholas Quentin Haas, Christopher G. Stahl, Spencer Paulissen, Prasanna Date, Thomas E. Potok, Shay Sneider:
Neuromorphic Computing for Autonomous Racing. 23:1-23:5 - Bill Kay, Catherine D. Schuman, Jade O'Connor, Prasanna Date, Thomas E. Potok:
Neuromorphic Graph Algorithms: Cycle Detection, Odd Cycle Detection, and Max Flow. 24:1-24:7 - Brian S. Robinson, Adam Polevoy, Sean McDaniel, Will Coon, Clara A. Scholl, Mark McLean, Erik Johnson:
A spiking network model for semantic representation and replay-based association acquisition. 25:1-25:8 - Brian Hoskins, Wen Ma, Mitchell Fream, Osama Yousuf, Matthew W. Daniels, Jonathan Goodwill, Advait Madhavan, Hoang Tung, Mark Branstad, Muqing Liu, Rasmus Madsen, Jabez Mclelland, Gina C. Adam, Martin Lueker-Boden:
A System for Validating Resistive Neural Network Prototypes. 26:1-26:5 - Ranajay Medya, Sai Sukruth Bezugam, Dwijay Bane, Manan Suri:
2D Histogram based Region Proposal (H2RP) Algorithm for Neuromorphic Vision Sensors. 27:1-27:6 - Terrence C. Stewart, Marc-Antoine Drouin, Guillaume Gagné, Guy Godin:
Drone Virtual Fence Using a Neuromorphic Camera. 28:1-28:9 - Nikhil Garg, Ismael Balafrej, Yann Beilliard, Dominique Drouin, Fabien Alibart, Jean Rouat:
Signals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition. 29:1-29:8
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