X-Ray scattering image classification using deep learning

Boyu Wang; Kevin Yager; Dantong Yu; Minh Hoai

doi:10.1109/WACV.2017.83

X-Ray scattering image classification using deep learning

Boyu Wang, Kevin Yager, Dantong Yu, Minh Hoai

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

47 Scopus citations

Abstract

Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing x-ray scattering images. In particular, we apply Convolutional Neural Networks and Convolutional Autoencoders for x-ray scattering image classification. To acquire enough training data for deep learning, we use simulation software to generate synthetic x-ray scattering images. Experiments show that deep learning methods outperform previously published methods by 10% on synthetic and real datasets.

Original language	English (US)
Title of host publication	Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	697-704
Number of pages	8
ISBN (Electronic)	9781509048229
DOIs	https://doi.org/10.1109/WACV.2017.83
State	Published - May 11 2017
Externally published	Yes
Event	17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017 - Santa Rosa, United States Duration: Mar 24 2017 → Mar 31 2017

Publication series

Name	Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017

Other

Other	17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017
Country/Territory	United States
City	Santa Rosa
Period	3/24/17 → 3/31/17

All Science Journal Classification (ASJC) codes

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.1109/WACV.2017.83

Cite this

Wang, B., Yager, K., Yu, D., & Hoai, M. (2017). X-Ray scattering image classification using deep learning. In Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017 (pp. 697-704). Article 7926666 (Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WACV.2017.83

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title = "X-Ray scattering image classification using deep learning",

abstract = "Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing x-ray scattering images. In particular, we apply Convolutional Neural Networks and Convolutional Autoencoders for x-ray scattering image classification. To acquire enough training data for deep learning, we use simulation software to generate synthetic x-ray scattering images. Experiments show that deep learning methods outperform previously published methods by 10% on synthetic and real datasets.",

author = "Boyu Wang and Kevin Yager and Dantong Yu and Minh Hoai",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017 ; Conference date: 24-03-2017 Through 31-03-2017",

year = "2017",

month = may,

day = "11",

doi = "10.1109/WACV.2017.83",

language = "English (US)",

series = "Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Wang, B, Yager, K, Yu, D & Hoai, M 2017, X-Ray scattering image classification using deep learning. in Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017., 7926666, Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017, Institute of Electrical and Electronics Engineers Inc., pp. 697-704, 17th IEEE Winter Conference on Applications of Computer Vision, WACV 2017, Santa Rosa, United States, 3/24/17. https://doi.org/10.1109/WACV.2017.83

X-Ray scattering image classification using deep learning. / Wang, Boyu; Yager, Kevin; Yu, Dantong et al.
Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 697-704 7926666 (Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - X-Ray scattering image classification using deep learning

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AU - Yager, Kevin

AU - Yu, Dantong

AU - Hoai, Minh

PY - 2017/5/11

Y1 - 2017/5/11

N2 - Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing x-ray scattering images. In particular, we apply Convolutional Neural Networks and Convolutional Autoencoders for x-ray scattering image classification. To acquire enough training data for deep learning, we use simulation software to generate synthetic x-ray scattering images. Experiments show that deep learning methods outperform previously published methods by 10% on synthetic and real datasets.

AB - Visual inspection of x-ray scattering images is a powerful technique for probing the physical structure of materials at the molecular scale. In this paper, we explore the use of deep learning to develop methods for automatically analyzing x-ray scattering images. In particular, we apply Convolutional Neural Networks and Convolutional Autoencoders for x-ray scattering image classification. To acquire enough training data for deep learning, we use simulation software to generate synthetic x-ray scattering images. Experiments show that deep learning methods outperform previously published methods by 10% on synthetic and real datasets.

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M3 - Conference contribution

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T3 - Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017

SP - 697

EP - 704

BT - Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017

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ER -

Wang B, Yager K, Yu D, Hoai M. X-Ray scattering image classification using deep learning. In Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 697-704. 7926666. (Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017). doi: 10.1109/WACV.2017.83

X-Ray scattering image classification using deep learning

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