March 14, 2024, 4:43 a.m. | Sadaf Moaveninejad, Andrea Janes, Camillo Porcaro

cs.LG updates on arXiv.org arxiv.org

arXiv:2301.10164v2 Announce Type: replace-cross
Abstract: Tracking climbers' activity to improve services and make the best use of their infrastructure is a concern for climbing gyms. Each climbing session must be analyzed from beginning till lowering of the climber. Therefore, spotting the climbers descending is crucial since it indicates when the ascent has come to an end. This problem must be addressed while preserving privacy and convenience of the climbers and the costs of the gyms. To this aim, a hardware …

abstract arxiv cs.ai cs.lg cs.ro detection eess.sp infrastructure sensor services session sport tracking type

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

Sr. VBI Developer II

@ Atos | Texas, US, 75093

Wealth Management - Data Analytics Intern/Co-op Fall 2024

@ Scotiabank | Toronto, ON, CA