4 citations · 6 across the 3 of their papers we have counts for
3 papers
SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception
Deepika Sharma, Shubham Negi, Trishit Dutta +2
Spiking Neural Networks (SNNs), with their inherent recurrence, offer an efficient method for processing the asynchronous temporal data generated by Dynamic Vision Sensors (DVS), m…
HCiM: ADC-Less Hybrid Analog-Digital Compute in Memory Accelerator for Deep Learning Workloads
Shubham Negi, Utkarsh Saxena, Deepika Sharma +1
Analog Compute-in-Memory (CiM) accelerators are increasingly recognized for their efficiency in accelerating Deep Neural Networks (DNN). However, their dependence on Analog-to-Digi…
Best of Both Worlds: Hybrid SNN-ANN Architecture for Event-based Optical Flow Estimation
Shubham Negi, Deepika Sharma, Adarsh Kumar Kosta +1
In the field of robotics, event-based cameras are emerging as a promising low-power alternative to traditional frame-based cameras for capturing high-speed motion and high dynamic…