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1
11K Hands: Gender recognition and biometric identification using a large dataset of hand images
11K Hands: Gender recognition and biometric identification using a large dataset of hand images
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11K Hands: Gender recognition and biometric identification using a large dataset of hand images

Multimedia tools and applications, 2019-08, Vol.78 (15), p.20835-20854 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Multimedia Tools and Applications is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-019-7424-8

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2
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets
16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets
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16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets

PloS one, 2015-02, Vol.10 (2), p.e0116106-e0116106 [Peer Reviewed Journal]

COPYRIGHT 2015 Public Library of Science ;COPYRIGHT 2015 Public Library of Science ;2015 Chaudhary et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2015 Chaudhary et al 2015 Chaudhary et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0116106 ;PMID: 25646627

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3
18F-FDG-PET/CT Whole-Body Imaging Lung Tumor Diagnostic Model: An Ensemble E-ResNet-NRC with Divided Sample Space
18F-FDG-PET/CT Whole-Body Imaging Lung Tumor Diagnostic Model: An Ensemble E-ResNet-NRC with Divided Sample Space
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18F-FDG-PET/CT Whole-Body Imaging Lung Tumor Diagnostic Model: An Ensemble E-ResNet-NRC with Divided Sample Space

BioMed research international, 2021-04, Vol.2021, p.1-13 [Peer Reviewed Journal]

Copyright © 2021 Zhou Tao et al. ;Copyright © 2021 Zhou Tao et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;Copyright © 2021 Zhou Tao et al. 2021 ;ISSN: 2314-6133 ;EISSN: 2314-6141 ;DOI: 10.1155/2021/8865237 ;PMID: 33869635

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4
2 Metagenomic Detection and Binning of Plasmids for an Improved Understanding of the Risk of Antimicrobial Resistance Gene Transfer Events
2 Metagenomic Detection and Binning of Plasmids for an Improved Understanding of the Risk of Antimicrobial Resistance Gene Transfer Events
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2 Metagenomic Detection and Binning of Plasmids for an Improved Understanding of the Risk of Antimicrobial Resistance Gene Transfer Events

Journal of animal science, 2023-11, Vol.101 (Supplement_2), p.62-62 [Peer Reviewed Journal]

The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. 2023 ;The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. ;ISSN: 0021-8812 ;EISSN: 1525-3163 ;DOI: 10.1093/jas/skad341.068

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5
20 - Forecast and prediction of COVID-19 using machine learning
20 - Forecast and prediction of COVID-19 using machine learning
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20 - Forecast and prediction of COVID-19 using machine learning

Data Science for COVID-19, 2021, p.381-397

2021 Elsevier Inc. ;ISBN: 9780128245361 ;ISBN: 0128245379 ;ISBN: 9780128245378 ;ISBN: 0128245360 ;DOI: 10.1016/B978-0-12-824536-1.00027-7

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6
2DPCANet: a deep leaning network for face recognition
2DPCANet: a deep leaning network for face recognition
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2DPCANet: a deep leaning network for face recognition

Multimedia tools and applications, 2018-05, Vol.77 (10), p.12919-12934 [Peer Reviewed Journal]

Springer Science+Business Media, LLC 2017 ;Multimedia Tools and Applications is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-017-4923-3

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7
3D Facial Expression Recognition Using Multi-channel Deep Learning Framework
3D Facial Expression Recognition Using Multi-channel Deep Learning Framework
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3D Facial Expression Recognition Using Multi-channel Deep Learning Framework

Circuits, systems, and signal processing, 2020-02, Vol.39 (2), p.789-804 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Circuits, Systems, and Signal Processing is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 0278-081X ;EISSN: 1531-5878 ;DOI: 10.1007/s00034-019-01144-8

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8
3D MAPPING OF BENTHIC HABITAT USING XGBOOST AND STRUCTURE FROM MOTION PHOTOGRAMMETRY
3D MAPPING OF BENTHIC HABITAT USING XGBOOST AND STRUCTURE FROM MOTION PHOTOGRAMMETRY
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3D MAPPING OF BENTHIC HABITAT USING XGBOOST AND STRUCTURE FROM MOTION PHOTOGRAMMETRY

ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, 2023-01, Vol.X-1/W1-2023, p.1131-1136 [Peer Reviewed Journal]

2023. This work is published under https://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: 2194-9050 ;ISSN: 2194-9042 ;EISSN: 2194-9050 ;DOI: 10.5194/isprs-annals-X-1-W1-2023-1131-2023

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9
3D Model Classification Based on Bayesian Classifier with AdaBoost
3D Model Classification Based on Bayesian Classifier with AdaBoost
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3D Model Classification Based on Bayesian Classifier with AdaBoost

Discrete dynamics in nature and society, 2021, Vol.2021, p.1-12 [Peer Reviewed Journal]

Copyright © 2021 Xue-Yao Gao et al. ;COPYRIGHT 2021 Hindawi Limited ;Copyright © 2021 Xue-Yao Gao et al. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 ;ISSN: 1026-0226 ;EISSN: 1607-887X ;DOI: 10.1155/2021/2154762

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10
3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology
3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology
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3D Simulations of Intracerebral Hemorrhage Detection Using Broadband Microwave Technology

Sensors (Basel, Switzerland), 2019-08, Vol.19 (16), p.3482 [Peer Reviewed Journal]

2019. This work is licensed under https://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. ;2019 by the authors. 2019 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s19163482 ;PMID: 31395840

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11
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar data
3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar data
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3DMASC: Accessible, explainable 3D point clouds classification. Application to Bi-spectral Topo-bathymetric lidar data

arXiv.org, 2024-01

2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2401.09481

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12
3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework
3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework
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3N-GAN: Semi-Supervised Classification of X-Ray Images with a 3-Player Adversarial Framework

arXiv.org, 2021-09

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. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2109.13862

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13
5G/B5G Service Classification Using Supervised Learning
5G/B5G Service Classification Using Supervised Learning
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5G/B5G Service Classification Using Supervised Learning

Applied sciences, 2021-06, Vol.11 (11), p.4942 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2076-3417 ;EISSN: 2076-3417 ;DOI: 10.3390/app11114942

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14
A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study
A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study
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A 10-Gene Classifier for Indeterminate Thyroid Nodules: Development and Multicenter Accuracy Study

Thyroid (New York, N.Y.), 2017-08, Vol.27 (8), p.158-1067 [Peer Reviewed Journal]

2017, Mary Ann Liebert, Inc. ;Hernán E. González . 2017; Published by Mary Ann Liebert, Inc. 2017 ;ISSN: 1050-7256 ;EISSN: 1557-9077 ;DOI: 10.1089/thy.2017.0067 ;PMID: 28521616

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15
A 2DCNN-RF Model for Offshore Wind Turbine High-Speed Bearing-Fault Diagnosis under Noisy Environment
A 2DCNN-RF Model for Offshore Wind Turbine High-Speed Bearing-Fault Diagnosis under Noisy Environment
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A 2DCNN-RF Model for Offshore Wind Turbine High-Speed Bearing-Fault Diagnosis under Noisy Environment

Energies (Basel), 2022-05, Vol.15 (9), p.3340 [Peer Reviewed Journal]

2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1996-1073 ;EISSN: 1996-1073 ;DOI: 10.3390/en15093340

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16
A 3D nodule candidate detection method supported by hybrid features to reduce false positives in lung nodule detection
A 3D nodule candidate detection method supported by hybrid features to reduce false positives in lung nodule detection
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A 3D nodule candidate detection method supported by hybrid features to reduce false positives in lung nodule detection

Multimedia tools and applications, 2019-09, Vol.78 (18), p.26287-26311 [Peer Reviewed Journal]

Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Multimedia Tools and Applications is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 1380-7501 ;EISSN: 1573-7721 ;DOI: 10.1007/s11042-019-07819-3

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17
A-PETE: Adaptive Prototype Explanations of Tree Ensembles
A-PETE: Adaptive Prototype Explanations of Tree Ensembles
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A-PETE: Adaptive Prototype Explanations of Tree Ensembles

arXiv.org, 2024-05

2024. 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. ;http://creativecommons.org/licenses/by/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2405.21036

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18
A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE
A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE
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A-SMOTE: A New Preprocessing Approach for Highly Imbalanced Datasets by Improving SMOTE

International journal of computational intelligence systems, 2019-01, Vol.12 (2), p.1412-1422 [Peer Reviewed Journal]

The Authors 2019 ;ISSN: 1875-6891 ;ISSN: 1875-6883 ;EISSN: 1875-6883 ;DOI: 10.2991/ijcis.d.191114.002

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19
A3T: Adversarially Augmented Adversarial Training
A3T: Adversarially Augmented Adversarial Training
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A3T: Adversarially Augmented Adversarial Training

arXiv.org, 2018-01

2018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.1801.04055

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20
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning
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ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning

arXiv.org, 2021-10

2021. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;http://arxiv.org/licenses/nonexclusive-distrib/1.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2110.10368

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