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1
Value Analysis and Mode Construction of Tutorial System for P2P Undergraduates in Computer Science--Based on the Reform Practice of Tutorial System in the College of Computer Science, Xi'an University of Technology
Value Analysis and Mode Construction of Tutorial System for P2P Undergraduates in Computer Science--Based on the Reform Practice of Tutorial System in the College of Computer Science, Xi'an University of Technology
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Value Analysis and Mode Construction of Tutorial System for P2P Undergraduates in Computer Science--Based on the Reform Practice of Tutorial System in the College of Computer Science, Xi'an University of Technology

Journal of physics. Conference series, 2020-06, Vol.1575 (1), p.12229 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1575/1/012229

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2
Research on the Development Trend of Computer Science and Technology in the "Internet +" Era
Research on the Development Trend of Computer Science and Technology in the "Internet +" Era
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Research on the Development Trend of Computer Science and Technology in the "Internet +" Era

Journal of physics. Conference series, 2020-11, Vol.1682 (1), p.12070 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1682/1/012070

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3
The 2nd International Conference on Mathematics, Science and Computer Science 2018
The 2nd International Conference on Mathematics, Science and Computer Science 2018
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The 2nd International Conference on Mathematics, Science and Computer Science 2018

Journal of physics. Conference series, 2019-07, Vol.1277 (1), p.11001 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1277/1/011001

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4
Application of a Novel and Improved VGG-19 Network in the Detection of Workers Wearing Masks
Application of a Novel and Improved VGG-19 Network in the Detection of Workers Wearing Masks
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Application of a Novel and Improved VGG-19 Network in the Detection of Workers Wearing Masks

Journal of Physics: Conference Series, 2020-04, Vol.1518 (1), p.12041-012041 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Published under licence by IOP Publishing Ltd 2020 ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1518/1/012041 ;PMID: 34191934

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5
Automatic Detection of Welding Defects using Deep Neural Network
Automatic Detection of Welding Defects using Deep Neural Network
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Automatic Detection of Welding Defects using Deep Neural Network

Journal of physics. Conference series, 2018-01, Vol.933 (1), p.12006 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/933/1/012006

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6
Machine Learning in High Energy Physics Community White Paper
Machine Learning in High Energy Physics Community White Paper
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Machine Learning in High Energy Physics Community White Paper

Journal of physics. Conference series, 2018-09, Vol.1085 (2), p.22008 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;ISSN: 1742-6596 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1085/2/022008

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7
The MLIP package: moment tensor potentials with MPI and active learning
The MLIP package: moment tensor potentials with MPI and active learning
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The MLIP package: moment tensor potentials with MPI and active learning

Machine learning: science and technology, 2021-06, Vol.2 (2), p.25002 [Peer Reviewed Journal]

2020 The Author(s). Published by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abc9fe ;CODEN: MLSTCK

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8
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
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Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation

Machine learning: science and technology, 2020-12, Vol.1 (4), p.45024 [Peer Reviewed Journal]

2020 The Author(s). Published by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/aba947 ;CODEN: MLSTCK

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9
A Survey on Application of Knowledge Graph
A Survey on Application of Knowledge Graph
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A Survey on Application of Knowledge Graph

Journal of physics. Conference series, 2020-03, Vol.1487 (1), p.12016 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1487/1/012016

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10
Machine Learning from Theory to Algorithms: An Overview
Machine Learning from Theory to Algorithms: An Overview
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Machine Learning from Theory to Algorithms: An Overview

Journal of physics. Conference series, 2018-11, Vol.1142 (1), p.12012 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1142/1/012012

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11
LiteRed 1.4: a powerful tool for reduction of multiloop integrals
LiteRed 1.4: a powerful tool for reduction of multiloop integrals
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LiteRed 1.4: a powerful tool for reduction of multiloop integrals

Journal of physics. Conference series, 2014-06, Vol.523 (1), p.12059-8 [Peer Reviewed Journal]

2014. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/523/1/012059

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12
Enhancing gravitational-wave science with machine learning
Enhancing gravitational-wave science with machine learning
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Enhancing gravitational-wave science with machine learning

Machine learning: science and technology, 2021-03, Vol.2 (1), p.11002 [Peer Reviewed Journal]

2020 The Author(s). Published by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abb93a ;CODEN: MLSTCK

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13
Keyword Based System to Enhance the Efficiency of Student's Performance Report in Computer Science Education
Keyword Based System to Enhance the Efficiency of Student's Performance Report in Computer Science Education
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Keyword Based System to Enhance the Efficiency of Student's Performance Report in Computer Science Education

Journal of physics. Conference series, 2019-06, Vol.1235 (1), p.12090 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1235/1/012090

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14
Prediction of chemical reaction yields using deep learning
Prediction of chemical reaction yields using deep learning
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Prediction of chemical reaction yields using deep learning

Machine learning: science and technology, 2021-03, Vol.2 (1), p.15016 [Peer Reviewed Journal]

2021. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abc81d

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15
Social VR : A New Form of Social Communication in the Future or a Beautiful Illusion?
Social VR : A New Form of Social Communication in the Future or a Beautiful Illusion?
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Social VR : A New Form of Social Communication in the Future or a Beautiful Illusion?

Journal of physics. Conference series, 2020-04, Vol.1518 (1), p.12032 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2020. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1518/1/012032

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16
Data-driven discovery of Koopman eigenfunctions for control
Data-driven discovery of Koopman eigenfunctions for control
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Data-driven discovery of Koopman eigenfunctions for control

Machine learning: science and technology, 2021-09, Vol.2 (3), p.35023 [Peer Reviewed Journal]

2021 The Author(s). Published by IOP Publishing Ltd ;2021. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abf0f5 ;CODEN: MLSTCK

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17
Methods for comparing uncertainty quantifications for material property predictions
Methods for comparing uncertainty quantifications for material property predictions
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Methods for comparing uncertainty quantifications for material property predictions

Machine learning: science and technology, 2020-06, Vol.1 (2), p.25006 [Peer Reviewed Journal]

2020 The Author(s). Published by IOP Publishing Ltd ;Copyright IOP Publishing Jun 2020 ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/ab7e1a ;CODEN: MLSTCK

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18
Deep learning in electron microscopy
Deep learning in electron microscopy
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Deep learning in electron microscopy

Machine learning: science and technology, 2021-03, Vol.2 (1), p.11004 [Peer Reviewed Journal]

ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abd614

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19
Understanding of Object Detection Based on CNN Family and YOLO
Understanding of Object Detection Based on CNN Family and YOLO
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Understanding of Object Detection Based on CNN Family and YOLO

Journal of physics. Conference series, 2018-04, Vol.1004 (1), p.12029 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1004/1/012029

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20
Unsupervised machine learning of topological phase transitions from experimental data
Unsupervised machine learning of topological phase transitions from experimental data
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Unsupervised machine learning of topological phase transitions from experimental data

Machine learning: science and technology, 2021-09, Vol.2 (3), p.35037 [Peer Reviewed Journal]

2021 The Author(s). Published by IOP Publishing Ltd ;ISSN: 2632-2153 ;EISSN: 2632-2153 ;DOI: 10.1088/2632-2153/abffe7 ;CODEN: MLSTCK

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