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Found 5 papers, 1 papers with code
A 51.3 TOPS/W, 134.4 GOPS In-memory Binary Image Filtering in 65nm CMOS
As compared to fully digital implementation, IMF enables > 70x energy savings and a > 3x improvement of processing time when tested with the video recordings from a DAVIS sensor and achieves a peak throughput of 134. 4 GOPS.
A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-time Systems
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.
EBBINNOT: A Hardware Efficient Hybrid Event-Frame Tracker for Stationary Dynamic Vision Sensors
To the best of our knowledge, this is the first time a stationary DVS based traffic monitoring solution is extensively compared to simultaneously recorded RGB frame-based methods while showing tremendous promise by outperforming state-of-the-art deep learning solutions.
HyNNA: Improved Performance for Neuromorphic Vision Sensor based Surveillance using Hybrid Neural Network Architecture
Applications in the Internet of Video Things (IoVT) domain have very tight constraints with respect to power and area.
A low-power end-to-end hybrid neuromorphic framework for surveillance applications
With the success of deep learning, object recognition systems that can be deployed for real-world applications are becoming commonplace.
