4 citations · 6 across the 5 of their papers we have counts for
5 papers
HOMI: Ultra-Fast EdgeAI platform for Event Cameras
Shankaranarayanan H, Satyapreet Singh Yadav, Adithya Krishna +3
Event cameras offer significant advantages for edge robotics applications due to their asynchronous operation and sparse, event-driven output, making them well-suited for tasks req…
Neural Signal Compression using RAMAN tinyML Accelerator for BCI Applications
Adithya Krishna, Sohan Debnath, Madhuvanthi Srivatsav +3
High-quality, multi-channel neural recording is indispensable for neuroscience research and clinical applications. Large-scale brain recordings often produce vast amounts of data t…
RAMAN: A Re-configurable and Sparse tinyML Accelerator for Inference on Edge
Adithya Krishna, Srikanth Rohit Nudurupati, Chandana D G +4
Deep Neural Network (DNN) based inference at the edge is challenging as these compute and data-intensive algorithms need to be implemented at low cost and low power while meeting t…
Source localization using particle filtering on FPGA for robotic navigation with imprecise binary measurement
Adithya Krishna, André van Schaik, Chetan Singh Thakur
Particle filtering is a recursive Bayesian estimation technique that has gained popularity recently for tracking and localization applications. It uses Monte Carlo simulation and h…
Unlimited Dynamic Range Analog-to-Digital Conversion
Adithya Krishna, Sunil Rudresh, Vishal Shaw +3
Analog-to-digital converters (ADCs) provide the link between continuous-time signals and their discrete-time counterparts, and the Shannon-Nyquist sampling theorem provides the mat…