Document Type
Conference Proceeding
Publication Date
1-1-2024
Journal / Book Title
Proceedings 2024 IEEE International Conference on Big Data Bigdata 2024
Abstract
This work demonstrates DISCERN (Detection Image System with Commonsense Efficient Ranking Network), a novel generalizable task-ranking approach to improve human-robot collaboration via "discern"-ing with commonsense knowledge (CSK) derived from huge data repositories, augmented with image models and other everyday premises. It is an explainable, efficient solution useful to dynamic multipurpose robots.
DOI
10.1109/BigData62323.2024.10826141
Journal ISSN / Book ISBN
85218074324 (Scopus)
Montclair State University Digital Commons Citation
Roychoudhury, Swagnik and Varde, Aparna S., "DISCERN for Generalizable Robotic Contexts" (2024). School of Computing Faculty Scholarship and Creative Works. 58.
https://digitalcommons.montclair.edu/computing-facpubs/58