Visualizing Color-wise Saliency of Black-Box Image Classification Models

10/06/2020
by   Yuhki Hatakeyama, et al.
0

Image classification based on machine learning is being commonly used. However, a classification result given by an advanced method, including deep learning, is often hard to interpret. This problem of interpretability is one of the major obstacles in deploying a trained model in safety-critical systems. Several techniques have been proposed to address this problem; one of which is RISE, which explains a classification result by a heatmap, called a saliency map, which explains the significance of each pixel. We propose MC-RISE (Multi-Color RISE), which is an enhancement of RISE to take color information into account in an explanation. Our method not only shows the saliency of each pixel in a given image as the original RISE does, but the significance of color components of each pixel; a saliency map with color information is useful especially in the domain where the color information matters (e.g., traffic-sign recognition). We implemented MC-RISE and evaluate them using two datasets (GTSRB and ImageNet) to demonstrate the effectiveness of our methods in comparison with existing techniques for interpreting image classification results.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 12

page 20

12/31/2017

Context aware saliency map generation using semantic segmentation

Saliency map detection, as a method for detecting important regions of a...
07/27/2018

Influence of Image Classification Accuracy on Saliency Map Estimation

Saliency map estimation in computer vision aims to estimate the location...
11/23/2020

SCGAN: Saliency Map-guided Colorization with Generative Adversarial Network

Given a grayscale photograph, the colorization system estimates a visual...
12/29/2017

Exploring the significance of using perceptually relevant image decolorization method for scene classification

A color image contains luminance and chrominance components representing...
08/23/2018

Maximal Jacobian-based Saliency Map Attack

The Jacobian-based Saliency Map Attack is a family of adversarial attack...
06/19/2018

RISE: Randomized Input Sampling for Explanation of Black-box Models

Deep neural networks are increasingly being used to automate data analys...
06/05/2020

Black-box Explanation of Object Detectors via Saliency Maps

We propose D-RISE, a method for generating visual explanations for the p...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.