PMAL: A proxy model active learning approach for vision based industrial applications
Deep Learning models' performance strongly correlate with availability of annotated data;
however, massive data labeling is laborious, expensive, and error-prone when performed by …
however, massive data labeling is laborious, expensive, and error-prone when performed by …
[PDF][PDF] PMAL: A Proxy Model Active Learning Approach for Vision Based Industrial Applications
A KHAN, IUL HAQ, T HUSSAIN, K MUHAMMAD… - 2022 - scholar.archive.org
Data acts as fuel for Deep Learning (DL) models and in today's era, the availability of huge
amount of multimedia data enable DL models to be applied in various realms of life [1, 2] …
amount of multimedia data enable DL models to be applied in various realms of life [1, 2] …
PMAL: A Proxy Model Active Learning Approach for Vision Based Industrial Applications
A Khan, IU Haq, T Hussain… - ACM Transactions …, 2022 - research.edgehill.ac.uk
Deep Learning models' performance strongly correlate with availability of annotated data;
however, massive data labeling is laborious, expensive, and error-prone when performed by …
however, massive data labeling is laborious, expensive, and error-prone when performed by …
PMAL: A Proxy Model Active Learning Approach for Vision Based Industrial Applications
A Khan, I Ul Haq, T Hussain… - ACM …, 2022 - scholarworks.bwise.kr
Deep Learning models' performance strongly correlate with availability of annotated data;
however, massive data labeling is laborious, expensive, and error-prone when performed by …
however, massive data labeling is laborious, expensive, and error-prone when performed by …