Web: http://arxiv.org/abs/2209.07383

Sept. 16, 2022, 1:15 a.m. | Wenguan Wang, Cheng Han, Tianfei Zhou, Dongfang Liu

cs.CV updates on arXiv.org arxiv.org

We devise deep nearest centroids (DNC), a conceptually elegant yet
surprisingly effective network for large-scale visual recognition, by
revisiting Nearest Centroids, one of the most classic and simple classifiers.
Current deep models learn the classifier in a fully parametric manner, ignoring
the latent data structure and lacking simplicity and explainability. DNC
instead conducts nonparametric, case-based reasoning; it utilizes sub-centroids
of training samples to describe class distributions and clearly explains the
classification as the proximity of test data and the class …

arxiv

More from arxiv.org / cs.CV updates on arXiv.org

Postdoctoral Fellow: ML for autonomous materials discovery

@ Lawrence Berkeley National Lab | Berkeley, CA

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Research Engineer - VFX, Neural Compositing

@ Flawless | Los Angeles, California, United States

[Job-TB] Senior Data Engineer

@ CI&T | Brazil

Data Analytics Engineer

@ The Fork | Paris, France