163 citations · 414 across the 31 of their papers we have counts for
33 papers
An Efficient Hash-based Data Structure for Dynamic Vision Sensors and its Application to Low-energy Low-memory Noise Filtering
Pradeep Kumar Gopalakrishnan, Chip-Hong Chang, Arindam Basu
Events generated by the Dynamic Vision Sensor (DVS) are generally stored and processed in two-dimensional data structures whose memory complexity and energy-per-event scale proport…
Intelligence Processing Units Accelerate Neuromorphic Learning
Pao-Sheng Vincent Sun, Alexander Titterton, Anjlee Gopiani +4
Spiking neural networks (SNNs) have achieved orders of magnitude improvement in terms of energy consumption and latency when performing inference with deep learning workloads. Erro…
Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions
Arindam Basu, Charlotte Frenkel, Lei Deng +1
In this paper, we reviewed Spiking neural network (SNN) integrated circuit designs and analyzed the trends among mixed-signal cores, fully digital cores and large-scale, multi-core…
DeepFreeze: Cold Boot Attacks and High Fidelity Model Recovery on Commercial EdgeML Device
Yoo-Seung Won, Soham Chatterjee, Dirmanto Jap +2
EdgeML accelerators like Intel Neural Compute Stick 2 (NCS) can enable efficient edge-based inference with complex pre-trained models. The models are loaded in the host (like Raspb…
A 51.3 TOPS/W, 134.4 GOPS In-memory Binary Image Filtering in 65nm CMOS
Sumon Kumar Bose, Deepak Singla, Arindam Basu
Neuromorphic vision sensors (NVS) can enable energy savings due to their event-driven that exploits the temporal redundancy in video streams from a stationary camera. However, nois…
Prospects for Analog Circuits in Deep Networks
Shih-Chii Liu, John Paul Strachan, Arindam Basu
Operations typically used in machine learning al-gorithms (e.g. adds and soft max) can be implemented bycompact analog circuits. Analog Application-Specific Integrated Circuit (ASI…