Image Processing, Computer Vision, and Deep Learning: new approaches to the analysis and physics interpretation of LHC events
This review introduces recent developments in the application of image processing, computer vision, and deep neural networks to the analysis and interpretation of particle collision events at the Large Hadron Collider (LHC). The link between LHC data analysis and computer vision techniques relies on...
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| Published in: | Journal of physics. Conference series Vol. 762; no. 1; pp. 12035 - 12044 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Bristol
IOP Publishing
01.10.2016
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| ISSN: | 1742-6588, 1742-6596 |
| Online Access: | Get full text |
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| Abstract | This review introduces recent developments in the application of image processing, computer vision, and deep neural networks to the analysis and interpretation of particle collision events at the Large Hadron Collider (LHC). The link between LHC data analysis and computer vision techniques relies on the concept of jet-images, building on the notion of a particle physics detector as a digital camera and the particles it measures as images. We show that state-of-the-art image classification techniques based on deep neural network architectures significantly improve the identification of highly boosted electroweak particles with respect to existing methods. Furthermore, we introduce new methods to visualize and interpret the high level features learned by deep neural networks that provide discrimination beyond physics- derived variables, adding a new capability to understand physics and to design more powerful classification methods at the LHC. |
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| AbstractList | This review introduces recent developments in the application of image processing, computer vision, and deep neural networks to the analysis and interpretation of particle collision events at the Large Hadron Collider (LHC). The link between LHC data analysis and computer vision techniques relies on the concept of jet-images, building on the notion of a particle physics detector as a digital camera and the particles it measures as images. We show that state-of-the-art image classification techniques based on deep neural network architectures significantly improve the identification of highly boosted electroweak particles with respect to existing methods. Furthermore, we introduce new methods to visualize and interpret the high level features learned by deep neural networks that provide discrimination beyond physics- derived variables, adding a new capability to understand physics and to design more powerful classification methods at the LHC. |
| Author | De Oliveira, L. Schwartzman, A. Nachman, B. Kagan, M. Mackey, L |
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| Cites_doi | 10.1088/1126-6708/2008/04/063 10.1088/0954-3899/39/6/063001 10.1007/JHEP02(2015)118 10.1088/1748-0221/10/08/P08010 10.1016/S0168-9002(96)00771-1 10.1007/JHEP03(2011)015 10.1088/1748-0221/11/04/P04008 10.1140/epjc/s10052-014-2792-8 10.1140/epjc/s10052-011-1661-y 10.1140/epjc/s10052-010-1314-6 10.1088/1748-0221/11/01/P01019 10.1016/j.cpc.2008.01.036 10.1162/neco.1989.1.4.541 |
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| References | Cacciari M (1) 2008; 0804 12 13 ATLAS Collaboration (2) 2016; 11 14 16 ATLAS Collaboration (5) 2015 Altheimer A (11) 2012; 39 Almeida L G (15) 2015 Oliveira L (17) 2015 Russakovsky O (6) 2015 CMS Collaboration (3) 2016; 11 7 8 9 CMS Collaboration (4) 2015; 10 10 |
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| SubjectTerms | Artificial neural networks Computer architecture Computer vision Data analysis Deep learning Digital cameras Digital imaging Image classification Image processing Large Hadron Collider Machine learning Neural networks Particle collisions Particle physics Physics |
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| Title | Image Processing, Computer Vision, and Deep Learning: new approaches to the analysis and physics interpretation of LHC events |
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