Feb. 15, 2024, 5:43 a.m. | Lukas S. Huber, Fred W. Mast, Felix A. Wichmann

cs.LG updates on arXiv.org arxiv.org

arXiv:2402.09303v1 Announce Type: cross
Abstract: Recent research has seen many behavioral comparisons between humans and deep neural networks (DNNs) in the domain of image classification. Often, comparison studies focus on the end-result of the learning process by measuring and comparing the similarities in the representations of object categories once they have been formed. However, the process of how these representations emerge$\unicode{x2014}$that is, the behavioral changes and intermediate stages observed during the acquisition$\unicode{x2014}$is less often directly and empirically compared.
Here we …

abstract arxiv classification comparison cs.ai cs.cv cs.lg divergence domain evidence focus humans image measuring networks neural networks process q-bio.nc research studies type unicode

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Software Engineer for AI Training Data (School Specific)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Python)

@ G2i Inc | Remote

Software Engineer for AI Training Data (Tier 2)

@ G2i Inc | Remote

Business Intelligence Analyst Insights & Reporting

@ Bertelsmann | Hilversum, NH, NL, 1217WP