all AI news
Tri-modal Confluence with Temporal Dynamics for Scene Graph Generation in Operating Rooms
April 16, 2024, 4:47 a.m. | Diandian Guo, Manxi Lin, Jialun Pei, He Tang, Yueming Jin, Pheng-Ann Heng
cs.CV updates on arXiv.org arxiv.org
Abstract: A comprehensive understanding of surgical scenes allows for monitoring of the surgical process, reducing the occurrence of accidents and enhancing efficiency for medical professionals. Semantic modeling within operating rooms, as a scene graph generation (SGG) task, is challenging since it involves consecutive recognition of subtle surgical actions over prolonged periods. To address this challenge, we propose a Tri-modal (i.e., images, point clouds, and language) confluence with Temporal dynamics framework, termed TriTemp-OR. Diverging from previous approaches …
abstract accidents arxiv confluence cs.cv dynamics efficiency graph medical modal modeling monitoring process professionals recognition semantic semantic modeling temporal type understanding
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Tableau/PowerBI Developer (A.Con)
@ KPMG India | Bengaluru, Karnataka, India
Software Engineer, Backend - Data Platform (Big Data Infra)
@ Benchling | San Francisco, CA