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Lọc theo: Tài liệu mới: Mới từ 3 tháng trước xóa Artificial Neural Networks xóa
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1
Penetration Testing Framework using the Q Learning Ensemble Deep CNN Discriminator Framework
Penetration Testing Framework using the Q Learning Ensemble Deep CNN Discriminator Framework
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Penetration Testing Framework using the Q Learning Ensemble Deep CNN Discriminator Framework

International journal of advanced computer science & applications, 2024-01, Vol.15 (3)

2024. This work is licensed 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: 2158-107X ;EISSN: 2156-5570 ;DOI: 10.14569/IJACSA.2024.0150385

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2
Deep Convolutional Neural Networks Fusion with Support Vector Machines and K-Nearest Neighbors for Precise Crop Leaf Disease Classification
Deep Convolutional Neural Networks Fusion with Support Vector Machines and K-Nearest Neighbors for Precise Crop Leaf Disease Classification
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Deep Convolutional Neural Networks Fusion with Support Vector Machines and K-Nearest Neighbors for Precise Crop Leaf Disease Classification

International journal of advanced computer science & applications, 2024-01, Vol.15 (3)

2024. This work is licensed 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: 2158-107X ;EISSN: 2156-5570 ;DOI: 10.14569/IJACSA.2024.0150356

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3
Automated Parkinson's Disease Detection: A Review of Techniques, Datasets, Modalities, and Open Challenges
Automated Parkinson's Disease Detection: A Review of Techniques, Datasets, Modalities, and Open Challenges
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Automated Parkinson's Disease Detection: A Review of Techniques, Datasets, Modalities, and Open Challenges

International journal on smart sensing and intelligent systems, 2024-01, Vol.17 (1) [Tạp chí có phản biện]

2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 1178-5608 ;DOI: 10.2478/ijssis-2024-0008

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4
A novel approach to recognition of Alzheimer's and Parkinson's diseases: random subspace ensemble classifier based on deep hybrid features with a super-resolution image
A novel approach to recognition of Alzheimer's and Parkinson's diseases: random subspace ensemble classifier based on deep hybrid features with a super-resolution image
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A novel approach to recognition of Alzheimer's and Parkinson's diseases: random subspace ensemble classifier based on deep hybrid features with a super-resolution image

PeerJ. Computer science, 2024-02, Vol.10, p.e1862-e1862 [Tạp chí có phản biện]

2024 Alhudhaif. ;2024 Alhudhaif. This is an open access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2024 Alhudhaif 2024 Alhudhaif ;EISSN: 2376-5992 ;DOI: 10.7717/peerj-cs.1862 ;PMID: 38435579

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5
Brain Tumor Detection and Categorization with Segmentation of Improved Unsupervised Clustering Approach and Machine Learning Classifier
Brain Tumor Detection and Categorization with Segmentation of Improved Unsupervised Clustering Approach and Machine Learning Classifier
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Brain Tumor Detection and Categorization with Segmentation of Improved Unsupervised Clustering Approach and Machine Learning Classifier

Bioengineering (Basel), 2024-03, Vol.11 (3), p.266 [Tạp chí có phản biện]

COPYRIGHT 2024 MDPI AG ;2024 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. ;2024 by the authors. 2024 ;ISSN: 2306-5354 ;EISSN: 2306-5354 ;DOI: 10.3390/bioengineering11030266 ;PMID: 38534540

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6
Performance Comparison of Deep Learning -Based Tabular Models for Building Mapping Using High-Resolution Red, Green, and Blue Imagery and the Geographic Object-Based Image Analysis Framework
Performance Comparison of Deep Learning -Based Tabular Models for Building Mapping Using High-Resolution Red, Green, and Blue Imagery and the Geographic Object-Based Image Analysis Framework
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Performance Comparison of Deep Learning -Based Tabular Models for Building Mapping Using High-Resolution Red, Green, and Blue Imagery and the Geographic Object-Based Image Analysis Framework

Remote sensing (Basel, Switzerland), 2024-03, Vol.16 (5), p.878 [Tạp chí có phản biện]

COPYRIGHT 2024 MDPI AG ;2024 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: 2072-4292 ;EISSN: 2072-4292 ;DOI: 10.3390/rs16050878

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7
SNC_Net: Skin Cancer Detection by Integrating Handcrafted and Deep Learning-Based Features Using Dermoscopy Images
SNC_Net: Skin Cancer Detection by Integrating Handcrafted and Deep Learning-Based Features Using Dermoscopy Images
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SNC_Net: Skin Cancer Detection by Integrating Handcrafted and Deep Learning-Based Features Using Dermoscopy Images

Mathematics (Basel), 2024-04, Vol.12 (7), p.1030 [Tạp chí có phản biện]

COPYRIGHT 2024 MDPI AG ;2024 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: 2227-7390 ;EISSN: 2227-7390 ;DOI: 10.3390/math12071030

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8
Multi-WiIR: Multi-User Identity Legitimacy Authentication Based on WiFi Device
Multi-WiIR: Multi-User Identity Legitimacy Authentication Based on WiFi Device
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Multi-WiIR: Multi-User Identity Legitimacy Authentication Based on WiFi Device

Future internet, 2024-04, Vol.16 (4), p.127 [Tạp chí có phản biện]

COPYRIGHT 2024 MDPI AG ;2024 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: 1999-5903 ;EISSN: 1999-5903 ;DOI: 10.3390/fi16040127

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9
Remote sensing image information extraction based on Compensated Fuzzy Neural Network and big data analytics
Remote sensing image information extraction based on Compensated Fuzzy Neural Network and big data analytics
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Remote sensing image information extraction based on Compensated Fuzzy Neural Network and big data analytics

BMC medical imaging, 2024-04, Vol.24 (1), p.86-86 [Tạp chí có phản biện]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed 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) 2024 ;ISSN: 1471-2342 ;EISSN: 1471-2342 ;DOI: 10.1186/s12880-024-01266-9 ;PMID: 38600525

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10
TXAI-ADV: Trustworthy XAI for Defending AI Models against Adversarial Attacks in Realistic CIoT
TXAI-ADV: Trustworthy XAI for Defending AI Models against Adversarial Attacks in Realistic CIoT
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TXAI-ADV: Trustworthy XAI for Defending AI Models against Adversarial Attacks in Realistic CIoT

Electronics (Basel), 2024-05, Vol.13 (9), p.1769 [Tạp chí có phản biện]

COPYRIGHT 2024 MDPI AG ;2024 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: 2079-9292 ;EISSN: 2079-9292 ;DOI: 10.3390/electronics13091769

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11
Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach
Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach
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Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach

BMC medical imaging, 2024-05, Vol.24 (1), p.104-104 [Tạp chí có phản biện]

2024. The Author(s). ;COPYRIGHT 2024 BioMed Central Ltd. ;2024. This work is licensed 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: 1471-2342 ;EISSN: 1471-2342 ;DOI: 10.1186/s12880-024-01274-9 ;PMID: 38702613

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12
Explainability-Informed Targeted Malware Misclassification
Explainability-Informed Targeted Malware Misclassification
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Explainability-Informed Targeted Malware Misclassification

arXiv.org, 2024-05

2024. This work is published under http://creativecommons.org/licenses/by-nc-sa/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-nc-sa/4.0 ;EISSN: 2331-8422 ;DOI: 10.48550/arxiv.2405.04010

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13
Mitigating Bias Using Model-Agnostic Data Attribution
Mitigating Bias Using Model-Agnostic Data Attribution
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Mitigating Bias Using Model-Agnostic Data Attribution

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.2405.05031

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