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Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments
Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments
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Survey and Performance Analysis of Deep Learning Based Object Detection in Challenging Environments

Sensors (Basel, Switzerland), 2021-07, Vol.21 (15), p.5116 [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. ;2021 by the authors. 2021 ;ISSN: 1424-8220 ;EISSN: 1424-8220 ;DOI: 10.3390/s21155116 ;PMID: 34372351

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Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images
Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images
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Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images

Scientific reports, 2022-11, Vol.12 (1), p.19200-19200, Article 19200 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022. 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. ;The Author(s) 2022 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-022-21848-3 ;PMID: 36357456

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3
Evaluating the effectiveness of stain normalization techniques in automated grading of invasive ductal carcinoma histopathological images
Evaluating the effectiveness of stain normalization techniques in automated grading of invasive ductal carcinoma histopathological images
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Evaluating the effectiveness of stain normalization techniques in automated grading of invasive ductal carcinoma histopathological images

Scientific reports, 2023-11, Vol.13 (1), p.20518-20518, Article 20518 [Peer Reviewed Journal]

2023. The Author(s). ;The Author(s) 2023. 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: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-023-46619-6 ;PMID: 37993544

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4
Surveillance of communicable diseases using social media: A systematic review
Surveillance of communicable diseases using social media: A systematic review
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Surveillance of communicable diseases using social media: A systematic review

PloS one, 2023-02, Vol.18 (2), p.e0282101-e0282101 [Peer Reviewed Journal]

Copyright: © 2023 Pilipiec et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ;COPYRIGHT 2023 Public Library of Science ;2023 Pilipiec 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. ;2023 Pilipiec et al 2023 Pilipiec et al ;2023 Pilipiec 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. ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0282101 ;PMID: 36827297

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5
Socioeconomic and environmental patterns behind H1N1 spreading in Sweden
Socioeconomic and environmental patterns behind H1N1 spreading in Sweden
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Socioeconomic and environmental patterns behind H1N1 spreading in Sweden

Scientific reports, 2021-11, Vol.11 (1), p.22512-22512, Article 22512 [Peer Reviewed Journal]

2021. The Author(s). ;The Author(s) 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. ;The Author(s) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-01857-4 ;PMID: 34795338

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6
Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths
Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths
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Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths

The Journal of emergency medicine, 2021-12, Vol.61 (6), p.763 [Peer Reviewed Journal]

ISSN: 0736-4679 ;ISSN: 1090-1280 ;EISSN: 2352-5029 ;DOI: 10.1016/j.jemermed.2021.09.004

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7
Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition
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Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition

Scientific data, 2023-06, Vol.10 (1), p.378-378, Article 378 [Peer Reviewed Journal]

2023. The Author(s). ;The Author(s) 2023. 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. ;The Author(s) 2023 ;ISSN: 2052-4463 ;EISSN: 2052-4463 ;DOI: 10.1038/s41597-023-02286-w ;PMID: 37311807

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