SOTAVerified

Networks with pixels embedding: a method to improve noise resistance in images classification

2020-05-24Code Available0· sign in to hype

Yang Liu, Hai-Long Tu, Chi-Chun Zhou, Yi Liu, Fu-Lin Zhang

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

In the task of image classification, usually, the network is sensitive to noises. For example, an image of cat with noises might be misclassified as an ostrich. Conventionally, to overcome the problem of noises, one uses the technique of data augmentation, that is, to teach the network to distinguish noises by adding more images with noises in the training dataset. In this work, we provide a noise-resistance network in images classification by introducing a technique of pixel embedding. We test the network with pixel embedding, which is abbreviated as the network with PE, on the mnist database of handwritten digits. It shows that the network with PE outperforms the conventional network on images with noises. The technique of pixel embedding can be used in many tasks of image classification to improve noise resistance.

Tasks

Reproductions