Feb. 28, 2024, 5:47 a.m. | Tianyi Zhao, Maoxun Yuan, Xingxing Wei

cs.CV updates on arXiv.org arxiv.org

arXiv:2401.10731v2 Announce Type: replace
Abstract: Object detection in visible (RGB) and infrared (IR) images has been widely applied in recent years. Leveraging the complementary characteristics of RGB and IR images, the object detector provides reliable and robust object localization from day to night. Existing fusion strategies directly inject RGB and IR images into convolution neural networks, leading to inferior detection performance. Since the RGB and IR features have modality-specific noise, these strategies will worsen the fused features along with the …

abstract arxiv cs.cv detection fusion images localization robust strategies type via

Data Scientist (m/f/x/d)

@ Symanto Research GmbH & Co. KG | Spain, Germany

Aumni - Site Reliability Engineer III - MLOPS

@ JPMorgan Chase & Co. | Salt Lake City, UT, United States

Senior Data Analyst

@ Teya | Budapest, Hungary

Technical Analyst (Data Analytics)

@ Contact Government Services | Chicago, IL

Engineer, AI/Machine Learning

@ Masimo | Irvine, CA, United States

Private Bank - Executive Director: Data Science and Client / Business Intelligence

@ JPMorgan Chase & Co. | Mumbai, Maharashtra, India