A hybrid neuromorphic object tracking and classification framework for real-time systems

• Main Authors: Ussa, Andres, Rajen, Chockalingam Senthil, Pulluri, Tarun, Singla, Deepak, Acharya, Jyotibdha, Chuanrong, Gideon Fu, Basu, Arindam, Ramesh, Bharath
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2023
• Subjects: Engineering::Electrical and electronic engineering; Neuromorphics; Proposals
• Online Access: https://hdl.handle.net/10356/170575
• Institution: Nanyang Technological University

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 platforms such as mobile nodes and remote security applications. To address this challenge, this article proposes a...