Computer Vision Model
Computer vision models aim to enable computers to "see" and interpret images, enabling applications ranging from medical diagnosis to autonomous driving. Current research emphasizes improving model robustness, addressing biases and ethical concerns in datasets, and enhancing explainability through techniques like class activation maps and contextual analysis. This field is crucial for advancing various scientific disciplines and practical applications, with ongoing efforts focused on improving accuracy, efficiency, and fairness across diverse datasets and tasks.
Papers
April 28, 2022
April 13, 2022
April 7, 2022
BankNote-Net: Open dataset for assistive universal currency recognition
Felipe Oviedo, Srinivas Vinnakota, Eugene Seleznev, Hemant Malhotra, Saqib Shaikh, Juan Lavista Ferres
Solving ImageNet: a Unified Scheme for Training any Backbone to Top Results
Tal Ridnik, Hussam Lawen, Emanuel Ben-Baruch, Asaf Noy
April 6, 2022
February 15, 2022
February 11, 2022
December 16, 2021
November 22, 2021