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Found 5 papers, 0 papers with code
An Efficient Hash-based Data Structure for Dynamic Vision Sensors and its Application to Low-energy Low-memory Noise Filtering
Events generated by the Dynamic Vision Sensor (DVS) are generally stored and processed in two-dimensional data structures whose memory complexity and energy-per-event scale proportionately with increasing sensor dimensions.
ADIC: Anomaly Detection Integrated Circuit in 65nm CMOS utilizing Approximate Computing
An additional 42% energy saving can be achieved when a lighter version of OPIUM method is used for training with the same number of data samples lead to no significant compromise on the quality of inference.
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.
ADEPOS: A Novel Approximate Computing Framework for Anomaly Detection Systems and its Implementation in 65nm CMOS
However, on the detection of anomalies, the complexity of the network and computing precision are adaptively increased for accurate predictions.
A Stacked Autoencoder Neural Network based Automated Feature Extraction Method for Anomaly detection in On-line Condition Monitoring
Most of these are handcrafted features, where these are manually obtained based on the nature of the raw data.
