Nov. 23, 2022, 2:15 a.m. | Xiaoshan Wu, Weihua He, Man Yao, Ziyang Zhang, Yaoyuan Wang, Guoqi Li

cs.CV updates on arXiv.org arxiv.org

Event cameras are considered to have great potential for computer vision and
robotics applications because of their high temporal resolution and low power
consumption characteristics. However, the event stream output from event
cameras has asynchronous, sparse characteristics that existing computer vision
algorithms cannot handle. Spiking neural network is a novel event-based
computational paradigm that is considered to be well suited for processing
event camera tasks. However, direct training of deep SNNs suffers from
degradation problems. This work addresses these problems …

arxiv network neural network prediction spiking neural network

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Data Engineer

@ Lemon.io | Remote: Europe, LATAM, Canada, UK, Asia, Oceania

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US