Event Probability Mask (EPM) and Event Denoising Convolutional Neural Network (EDnCNN) for Neuromorphic Cameras

This paper presents a novel method for labeling real-world neuromorphic camera sensor data by calculating the likelihood of generating an event at each pixel within a short time window, which we refer to as "event probability mask" or EPM. Its applications include (i) objective benchmarkin...

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Vydané v:	Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) s. 1698 - 1707
Hlavní autori:	Baldwin, R. Wes, Almatrafi, Mohammed, Asari, Vijayan, Hirakawa, Keigo
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2020
Predmet:	Benchmark testing Cameras Hardware Neuromorphics Noise measurement Noise reduction Voltage control
ISSN:	1063-6919
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