Results 11 to 20 of about 25,780,245 (278)
Data-Driven Technology in Event-Based Vision [PDF]
Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness.
Ruolin Sun +4 more
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Event-Based Vision: Understanding Network Traffic Characteristics [PDF]
Event-based vision fosters a new way of sensing reality. Event-based cameras work radically differently compared to legacy frame-based cameras because they continuously measure brightness changes at a per-pixel granularity (i.e., events) rather than snapshots of intensity measurements (i.e., frames).
Giulia Attanasio +2 more
core +5 more sources
CSTR: A Compact Spatio-Temporal Representation for Event-Based Vision
Event-based vision is a novel perception modality that offers several advantages, such as high dynamic range and robustness to motion blur. In order to process events in batches and utilize modern computer vision deep-learning architectures, an ...
Zaid A. El Shair +2 more
doaj +2 more sources
An Artificial Neural SLAM Framework for Event-Based Vision
The SLAM problem for autonomous robots can be greatly improved by using event-based cameras. Compared to others, event-based cameras consume very low power while providing great temporal resolution and dynamic range.
Aykut G. Gelen, Ayten Atasoy
doaj +3 more sources
Event-Based Machine Vision for Edge AI Computing
Event-based sensors provide sparse, motion-centric measurements that can reduce data bandwidth and enable always-on perception on resource-constrained edge devices.
Paul K. J. Park +3 more
doaj +4 more sources
Event-based vision for Robotics
Event cameras, such as the Dynamic Vision Sensor (DVS), are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames.
Gallego Bonet, Guillermo
openaire +2 more sources
Event-based vision sensors (EVSs), with the core advantages of low latency, high dynamic range, and low data volume, have become one of the research hotspots in the field of computer vision.
Dongchao Gong +2 more
doaj +2 more sources
Experiencing Prosthetic Vision with Event-Based Sensors [PDF]
ICONS '22: Proceedings of the International Conference on Neuromorphic Systems (Knoxville TN USA July 27-29, 2022)
Rueckauer, Bodo, van Gerven, Marcel
openaire +1 more source
Neuromorphic vision: From sensors to event‐based algorithms
Regardless of the marvels brought by the conventional frame‐based cameras, they have significant drawbacks due to their redundancy in data and temporal latency. This causes problem in applications where low‐latency transmission and high‐speed processing are mandatory.
Lakshmi, Annamalai +2 more
openaire +4 more sources
Event-Based Feature Extraction Using Adaptive Selection Thresholds
Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware. However, not designed
Saeed Afshar +5 more
doaj +1 more source

