6 citations · 9 across the 2 of their papers we have counts for
3 papers
A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-time Systems
Andres Ussa, Chockalingam Senthil Rajen, Deepak Singla +4
Deep learning inference that needs to largely take place on the 'edge' is a highly computational and memory intensive workload, making it intractable for low-power, embedded platfo…
HyNNA: Improved Performance for Neuromorphic Vision Sensor based Surveillance using Hybrid Neural Network Architecture
Deepak Singla, Soham Chatterjee, Lavanya Ramapantulu +3
Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area. While neuromorphic vision sensors (NVS) may offer advantages…
A low-power end-to-end hybrid neuromorphic framework for surveillance applications
Andres Ussa, Luca Della Vedova, Vandana Reddy Padala +6
With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace. However, inference that needs to largely ta…