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Results 1 - 20 of 332  for All Library Resources

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1
Innovative Decision Fusion for Accurate Crop/Vegetation Classification with Multiple Classifiers and Multisource Remote Sensing Data
Innovative Decision Fusion for Accurate Crop/Vegetation Classification with Multiple Classifiers and Multisource Remote Sensing Data
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Innovative Decision Fusion for Accurate Crop/Vegetation Classification with Multiple Classifiers and Multisource Remote Sensing Data

Remote sensing (Basel, Switzerland), 2024-05, Vol.16 (9), p.1579 [Peer Reviewed Journal]

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/rs16091579

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2
Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers
Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers
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Using Longitudinal Twitter Data for Digital Epidemiology of Childhood Health Outcomes: An Annotated Data Set and Deep Neural Network Classifiers

Journal of medical Internet research, 2024-03, Vol.26 (4), p.e50652-e50652 [Peer Reviewed Journal]

Ari Z Klein, José Agustín Gutiérrez Gómez, Lisa D Levine, Graciela Gonzalez-Hernandez. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.03.2024. ;COPYRIGHT 2024 Journal of Medical Internet Research ;Ari Z Klein, José Agustín Gutiérrez Gómez, Lisa D Levine, Graciela Gonzalez-Hernandez. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 25.03.2024. 2024 ;ISSN: 1439-4456 ;EISSN: 1438-8871 ;DOI: 10.2196/50652 ;PMID: 38526542

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3
MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes
MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes
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MetageNN: a memory-efficient neural network taxonomic classifier robust to sequencing errors and missing genomes

BMC bioinformatics, 2024-04, Vol.25 (Suppl 1), p.153-153 [Peer Reviewed Journal]

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: 1471-2105 ;EISSN: 1471-2105 ;DOI: 10.1186/s12859-024-05760-3 ;PMID: 38627615

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4
Hyperspectral Image Classification with the Orthogonal Self-Attention ResNet and Two-Step Support Vector Machine
Hyperspectral Image Classification with the Orthogonal Self-Attention ResNet and Two-Step Support Vector Machine
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Hyperspectral Image Classification with the Orthogonal Self-Attention ResNet and Two-Step Support Vector Machine

Remote sensing (Basel, Switzerland), 2024-03, Vol.16 (6), p.1010 [Peer Reviewed Journal]

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/rs16061010

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5
Tumor cell type and gene marker identification by single layer perceptron neural network on single-cell RNA sequence data
Tumor cell type and gene marker identification by single layer perceptron neural network on single-cell RNA sequence data
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Tumor cell type and gene marker identification by single layer perceptron neural network on single-cell RNA sequence data

Journal of biosciences, 2024-06, Vol.49 (2), p.47 [Peer Reviewed Journal]

Indian Academy of Sciences 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. ;ISSN: 0250-5991 ;EISSN: 0973-7138 ;DOI: 10.1007/s12038-023-00368-w ;PMID: 38525885

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6
Effect of Texture Feature Distribution on Agriculture Field Type Classification with Multitemporal UAV RGB Images
Effect of Texture Feature Distribution on Agriculture Field Type Classification with Multitemporal UAV RGB Images
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Effect of Texture Feature Distribution on Agriculture Field Type Classification with Multitemporal UAV RGB Images

Remote sensing (Basel, Switzerland), 2024-04, Vol.16 (7), p.1221 [Peer Reviewed Journal]

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/rs16071221

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7
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 [Peer Reviewed Journal]

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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8
Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study
Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study
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Analyzing EEG patterns in young adults exposed to different acrophobia levels: a VR study

Frontiers in human neuroscience, 2024-05, Vol.18, p.1348154-1348154 [Peer Reviewed Journal]

Copyright © 2024 Russo, Tibermacine, Tibermacine, Chebana, Nahili, Starczewscki and Napoli. ;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. ;Copyright © 2024 Russo, Tibermacine, Tibermacine, Chebana, Nahili, Starczewscki and Napoli. 2024 Russo, Tibermacine, Tibermacine, Chebana, Nahili, Starczewscki and Napoli ;ISSN: 1662-5161 ;EISSN: 1662-5161 ;DOI: 10.3389/fnhum.2024.1348154 ;PMID: 38770396

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9
Evaluation of the Relation between Ictal EEG Features and XAI Explanations
Evaluation of the Relation between Ictal EEG Features and XAI Explanations
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Evaluation of the Relation between Ictal EEG Features and XAI Explanations

Brain sciences, 2024-04, Vol.14 (4), p.306 [Peer Reviewed Journal]

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: 2076-3425 ;EISSN: 2076-3425 ;DOI: 10.3390/brainsci14040306 ;PMID: 38671958

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10
Convolutional neural network-based magnetic resonance image differentiation of filum terminale ependymomas from schwannomas
Convolutional neural network-based magnetic resonance image differentiation of filum terminale ependymomas from schwannomas
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Convolutional neural network-based magnetic resonance image differentiation of filum terminale ependymomas from schwannomas

BMC cancer, 2024-03, Vol.24 (1), p.350-350 [Peer Reviewed Journal]

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: 1471-2407 ;EISSN: 1471-2407 ;DOI: 10.1186/s12885-024-12023-0 ;PMID: 38504164

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11
BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification
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BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification

RNA biology, 2024, Vol.21 (1), p.1-12 [Peer Reviewed Journal]

2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 2024 The Author(s) ;ISSN: 1547-6286 ;EISSN: 1555-8584 ;DOI: 10.1080/15476286.2024.2329451 ;PMID: 38528797

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12
Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis
Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis
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Ensemble-imbalance-based classification for amyotrophic lateral sclerosis prognostic prediction: identifying short-survival patients at diagnosis

BMC medical informatics and decision making, 2024-03, Vol.24 (1), p.80-80 [Peer Reviewed Journal]

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: 1472-6947 ;EISSN: 1472-6947 ;DOI: 10.1186/s12911-024-02484-5 ;PMID: 38504285

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13
Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer
Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer
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Deep transfer learning with fuzzy ensemble approach for the early detection of breast cancer

BMC medical imaging, 2024-04, Vol.24 (1), p.82-82 [Peer Reviewed Journal]

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/s12880-024-01267-8 ;PMID: 38589813

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14
Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization
Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization
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Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization

NPJ precision oncology, 2024-05, Vol.8 (1), p.106-106 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 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. ;The Author(s) 2024 ;ISSN: 2397-768X ;EISSN: 2397-768X ;DOI: 10.1038/s41698-024-00589-8 ;PMID: 38762647

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15
Explainable Automatic Detection of Fiber–Cement Roofs in Aerial RGB Images
Explainable Automatic Detection of Fiber–Cement Roofs in Aerial RGB Images
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Explainable Automatic Detection of Fiber–Cement Roofs in Aerial RGB Images

Remote sensing (Basel, Switzerland), 2024-04, Vol.16 (8), p.1342 [Peer Reviewed Journal]

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/rs16081342

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16
Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning
Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning
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Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning

Remote sensing (Basel, Switzerland), 2024-04, Vol.16 (8), p.1421 [Peer Reviewed Journal]

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/rs16081421

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17
Refined Detection and Classification of Knee Ligament Injury Based on ResNet Convolutional Neural Networks
Refined Detection and Classification of Knee Ligament Injury Based on ResNet Convolutional Neural Networks
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Refined Detection and Classification of Knee Ligament Injury Based on ResNet Convolutional Neural Networks

Life (Basel, Switzerland), 2024-04, Vol.14 (4), p.478 [Peer Reviewed Journal]

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: 2075-1729 ;EISSN: 2075-1729 ;DOI: 10.3390/life14040478 ;PMID: 38672749

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18
Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification
Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification
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Advancing Dermatological Diagnostics: Interpretable AI for Enhanced Skin Lesion Classification

Diagnostics (Basel), 2024-04, Vol.14 (7), p.753 [Peer Reviewed Journal]

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: 2075-4418 ;EISSN: 2075-4418 ;DOI: 10.3390/diagnostics14070753 ;PMID: 38611666

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19
Identification of Dominant Species and Their Distributions on an Uninhabited Island Based on Unmanned Aerial Vehicles and Machine Learning Models
Identification of Dominant Species and Their Distributions on an Uninhabited Island Based on Unmanned Aerial Vehicles and Machine Learning Models
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Identification of Dominant Species and Their Distributions on an Uninhabited Island Based on Unmanned Aerial Vehicles and Machine Learning Models

Remote sensing (Basel, Switzerland), 2024-05, Vol.16 (10), p.1652 [Peer Reviewed Journal]

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/rs16101652

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20
Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors
Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors
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Deep learning-based predictive classification of functional subpopulations of hematopoietic stem cells and multipotent progenitors

Stem cell research & therapy, 2024-03, Vol.15 (1), p.74-74 [Peer Reviewed Journal]

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: 1757-6512 ;EISSN: 1757-6512 ;DOI: 10.1186/s13287-024-03682-8 ;PMID: 38475857

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