22 citations · 31 across the 3 of their papers we have counts for
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cs.CV2020★ 3 cited
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…
cs.CV2019★ 6 cited
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…