Multiple auxiliary classifiers GAN for controllable imagegeneration: Application to license plate recognition
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Date
2021
Authors
Shvai, Nadiya
Hasnat, Abul
Nakib, Amir
Journal Title
Journal ISSN
Volume Title
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Abstract
One of the main challenges in developing machine learning (ML) applications is the lack of labeled and balanced datasets. In the literature, different techniques tackle this problem
via augmentation, rendering, and over-sampling. Still, these methods produce datasets that appear less natural, exhibit poor balance, and have less variation. One potential solution is
to leverage the Generative Adversarial Network (GAN) which achieves remarkable results in the generation of high-fidelity natural images. However, expanding the ability of GANs’
to control generated image attributes with supervisory information remains a challenge. This research aims to propose an efficient method to generate high-fidelity natural images
with total control of its main attributes. Therefore, this paper proposes a novel Multiple Auxiliary Classifiers GAN (MAC-GAN) framework based on Auxiliary Classifier GAN
(AC-GAN), multi-conditioning, Wasserstein distance, gradient penalty, and dynamic loss. It is therefore presented as an efficient solution for highly controllable image synthesis red
that allows to enrich and re-balance datasets beyond data augmentation. Furthermore, the effectiveness of MAC-GAN images on a target ML application called Automatic License
Plate Recognition (ALPR) under limited resource constraints is probed. The improvement achieved is over 5% accuracy, which is mainly due to the ability of the MAC-GAN to create
a balanced dataset with controllable synthesis and produce multiple (different) images with the same attributes, thus increasing the variation of the dataset in a more elaborate way
than data augmentation techniques.
Description
Keywords
machine learning (ML), labeled and balanced datasets, Generative Adversarial Network (GAN), Auxiliary Classifiers GAN (MAC-GAN), Plate Recognition (ALPR), article
Citation
Shvai N. Multiple auxiliary classifiers GAN for controllable imagegeneration: Application to license plate recognition / Nadiya Shvai, Abul Hasnat, Amir Nakib // IET Intelligent Transport Systems,. - 2022. - Vol. 17 (1). - P. 243-254. - https://doi.org/10.1049/itr2.12251