Results 1 - 20 of 8,611 for All Library Resources
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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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Material Type: Article
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InceptionTime: Finding AlexNet for time series classificationData mining and knowledge discovery, 2020-11, Vol.34 (6), p.1936-1962 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00710-yFull text available |
| 2 |
Material Type: Article
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ROCKET: exceptionally fast and accurate time series classification using random convolutional kernelsData mining and knowledge discovery, 2020-09, Vol.34 (5), p.1454-1495 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00701-zFull text available |
| 3 |
Material Type: Article
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Deep learning for time series classification: a reviewData mining and knowledge discovery, 2019-07, Vol.33 (4), p.917-963 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2019 ;Data Mining and Knowledge Discovery is a copyright of Springer, (2019). All Rights Reserved. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-019-00619-1Full text available |
| 4 |
Material Type: Article
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The great time series classification bake off: a review and experimental evaluation of recent algorithmic advancesData mining and knowledge discovery, 2017-05, Vol.31 (3), p.606-660 [Peer Reviewed Journal]The Author(s) 2016 ;Data Mining and Knowledge Discovery is a copyright of Springer, 2017. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-016-0483-9 ;PMID: 30930678Full text available |
| 5 |
Material Type: Article
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catch22: CAnonical Time-series CHaracteristics: Selected through highly comparative time-series analysisData mining and knowledge discovery, 2019-11, Vol.33 (6), p.1821-1852 [Peer Reviewed Journal]The Author(s) 2019 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-019-00647-xFull text available |
| 6 |
Material Type: Article
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On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical studyData mining and knowledge discovery, 2016-07, Vol.30 (4), p.891-927 [Peer Reviewed Journal]The Author(s) 2016 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-015-0444-8Full text available |
| 7 |
Material Type: Article
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Characterizing concept driftData mining and knowledge discovery, 2016-07, Vol.30 (4), p.964-994 [Peer Reviewed Journal]The Author(s) 2016 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-015-0448-4Full text available |
| 8 |
Material Type: Article
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A machine learning forecasting model for COVID-19 pandemic in IndiaStochastic environmental research and risk assessment, 2020, Vol.34 (7), p.959-972 [Peer Reviewed Journal]Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 1436-3240 ;EISSN: 1436-3259 ;DOI: 10.1007/s00477-020-01827-8 ;PMID: 32837309Full text available |
| 9 |
Material Type: Article
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The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advancesData mining and knowledge discovery, 2021-03, Vol.35 (2), p.401-449 [Peer Reviewed Journal]The Author(s) 2020 ;The Author(s) 2020. ;The Author(s) 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: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00727-3 ;PMID: 33679210Full text available |
| 10 |
Material Type: Book
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Statistical and Computational Inverse ProblemsSpringer Science+Business Media, Inc. 2005 ;ISSN: 0066-5452 ;ISBN: 0387220739 ;ISBN: 9780387220734 ;EISBN: 0387271325 ;EISBN: 9780387271323 ;DOI: 10.1007/b138659Full text available |
| 11 |
Material Type: Article
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Deep learning for real-time fruit detection and orchard fruit load estimation: benchmarking of ‘MangoYOLO’Precision agriculture, 2019-12, Vol.20 (6), p.1107-1135 [Peer Reviewed Journal]Springer Science+Business Media, LLC, part of Springer Nature 2019 ;Precision Agriculture is a copyright of Springer, (2019). All Rights Reserved. ;ISSN: 1385-2256 ;EISSN: 1573-1618 ;DOI: 10.1007/s11119-019-09642-0Full text available |
| 12 |
Material Type: Article
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TS-CHIEF: a scalable and accurate forest algorithm for time series classificationData mining and knowledge discovery, 2020-05, Vol.34 (3), p.742-775 [Peer Reviewed Journal]The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020 ;The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2020. ;Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-020-00679-8Full text available |
| 13 |
Material Type: Article
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MultiRocket: multiple pooling operators and transformations for fast and effective time series classificationData mining and knowledge discovery, 2022-09, Vol.36 (5), p.1623-1646 [Peer Reviewed Journal]Crown 2022 ;Crown 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. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-022-00844-1Full text available |
| 14 |
Material Type: Article
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Graph based anomaly detection and description: a surveyData mining and knowledge discovery, 2015-05, Vol.29 (3), p.626-688 [Peer Reviewed Journal]The Author(s) 2014 ;The Author(s) 2015 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-014-0365-yFull text available |
| 15 |
Material Type: Article
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New horizons in cosmology with spectral distortions of the cosmic microwave backgroundExperimental astronomy, 2021-06, Vol.51 (3), p.1515-1554 [Peer Reviewed Journal]The Author(s) 2021 ;ISSN: 0922-6435 ;EISSN: 1572-9508 ;DOI: 10.1007/s10686-021-09729-5Digital Resources/Online E-Resources |
| 16 |
Material Type: Article
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The BOSS is concerned with time series classification in the presence of noiseData mining and knowledge discovery, 2015-11, Vol.29 (6), p.1505-1530 [Peer Reviewed Journal]The Author(s) 2014 ;The Author(s) 2015 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-014-0377-7Full text available |
| 17 |
Material Type: Article
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Time series classification with ensembles of elastic distance measuresData mining and knowledge discovery, 2015-05, Vol.29 (3), p.565-592 [Peer Reviewed Journal]The Author(s) 2014 ;The Author(s) 2015 ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-014-0361-2Full text available |
| 18 |
Material Type: Article
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A review on distance based time series classificationData mining and knowledge discovery, 2019-03, Vol.33 (2), p.378-412 [Peer Reviewed Journal]The Author(s) 2018 ;Data Mining and Knowledge Discovery is a copyright of Springer, (2018). All Rights Reserved. ;ISSN: 1384-5810 ;EISSN: 1573-756X ;DOI: 10.1007/s10618-018-0596-4Full text available |
| 19 |
Material Type: Article
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Fast and accurate detection of kiwifruit in orchard using improved YOLOv3-tiny modelPrecision agriculture, 2021-06, Vol.22 (3), p.754-776 [Peer Reviewed Journal]Springer Science+Business Media, LLC, part of Springer Nature 2020 ;Springer Science+Business Media, LLC, part of Springer Nature 2020. ;ISSN: 1385-2256 ;EISSN: 1573-1618 ;DOI: 10.1007/s11119-020-09754-yFull text available |
| 20 |
Material Type: Article
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Unveiling the gravitational universe at μ-Hz frequenciesExperimental astronomy, 2021-06, Vol.51 (3), p.1333-1383 [Peer Reviewed Journal]The Author(s) 2021 ;Attribution ;ISSN: 0922-6435 ;EISSN: 1572-9508 ;DOI: 10.1007/s10686-021-09709-9Digital Resources/Online E-Resources |
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