18 citations · 32 across the 8 of their papers we have counts for
8 papers
Acoustic Imaging for UAV Detection: Dense Beamformed Energy Maps and U-Net SELD
Belman Jahir Rodriguez, Sergio F. Chevtchenko, Marcelo Herrera Martinez +2
We introduce a U-net model for 360° acoustic source localization formulated as a spherical semantic segmentation task. Rather than regressing discrete direction-of-arrival (DoA) an…
NeuroMorse: A Temporally Structured Dataset For Neuromorphic Computing
Ben Walters, Yeshwanth Bethi, Taylor Kergan +5
Neuromorphic engineering aims to advance computing by mimicking the brain's efficient processing, where data is encoded as asynchronous temporal events. This eliminates the need fo…
A Neuromorphic Architecture for Reinforcement Learning from Real-Valued Observations
Sergio F. Chevtchenko, Yeshwanth Bethi, Teresa B. Ludermir +1
Reinforcement Learning (RL) provides a powerful framework for decision-making in complex environments. However, implementing RL in hardware-efficient and bio-inspired ways remains…
Efficient Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA
Ali Mehrabi, Yeshwanth Bethi, André van Schaik +2
This paper presents an efficient hardware implementation of the recently proposed Optimized Deep Event-driven Spiking Neural Network Architecture (ODESA). ODESA is the first networ…
Event-driven Spectrotemporal Feature Extraction and Classification using a Silicon Cochlea Model
Ying Xu, Samalika Perera, Yeshwanth Bethi +2
This paper presents a reconfigurable digital implementation of an event-based binaural cochlear system on a Field Programmable Gate Array (FPGA). It consists of a pair of the Casca…
An optimised deep spiking neural network architecture without gradients
Yeshwanth Bethi, Ying Xu, Gregory Cohen +2
We present an end-to-end trainable modular event-driven neural architecture that uses local synaptic and threshold adaptation rules to perform transformations between arbitrary spa…
Real-Time Object Detection and Localization in Compressive Sensed Video on Embedded Hardware
Yeshwanth Ravi Theja Bethi, Sathyaprakash Narayanan, Venkat Rangan +1
Every day around the world, interminable terabytes of data are being captured for surveillance purposes. A typical 1-2MP CCTV camera generates around 7-12GB of data per day. Frame-…
A Compressive Sensing Video dataset using Pixel-wise coded exposure
Sathyaprakash Narayanan, Yeshwanth Bethi, Chetan Singh Thakur
Manifold amount of video data gets generated every minute as we read this document, ranging from surveillance to broadcasting purposes. There are two roadblocks that restrain us fr…