Fred Hohman

Interactive Classification for Deep Learning Interpretation

Demo, Conference on Computer Vision and Pattern Recognition (CVPR), 2018

Abstract

We present an interactive system enabling users to manipulate images to explore the robustness and sensitivity of deep learning image classifiers. Using modern web technologies to run in-browser inference, users can remove image features using inpainting algorithms to obtain new classifications in real time. This system allows users to compare and contrast what image regions humans and machine learning models use for classification.

Materials

Project
Demo
PDF
Video
Code

BibTeX

			
@article{cabrera2018interactive,
    title={Interactive Classification for Deep Learning Interpretation},
    author={Cabrera, {\'A}ngel and Hohman, Fred and Lin, Jason and Chau, Duen Horng},
    journal={Demo, IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2018},
    publisher={IEEE}
}