Katalog der Deutschen Nationalbibliothek

Neuigkeiten Servicezeiten in Frankfurt am Main ab 1. Dezember 2025: Montag bis Freitag 9–18 Uhr und Samstag 10–16 Uhr
Service hours in Frankfurt am Main from 1 December 2025: Monday to Friday 9:00-18:00 and Saturday 10:00-16:00
 
Neuigkeiten Wegen Wartungsarbeiten ist vom 12. bis 14. Januar 2026 der Museumslesesaal, sowie vom 14. bis 16. Januar 2026 der Musiklesesaal geschlossen. // Due to maintenance work the museum reading room will be closed from 12 to 14 January 2026 and the music reading room from 14 to 16 January 2026.
 
 

Ergebnis der Suche nach: tit all "Smart Data Analytics"



Treffer 5 von 99 < < > <



Online Ressourcen
Link zu diesem Datensatz https://d-nb.info/1322012261
Titel Smart Big Data in Digital Agriculture Applications : Acquisition, Advanced Analytics, and Plant Physiology-informed Artificial Intelligence / by Haoyu Niu, YangQuan Chen
Person(en) Niu, Haoyu (Verfasser)
Chen, Yangquan (Verfasser)
Organisation(en) SpringerLink (Online service) (Sonstige)
Ausgabe 1st ed. 2024
Verlag Cham : Springer Nature Switzerland, Imprint: Springer
Zeitliche Einordnung Erscheinungsdatum: 2024
Umfang/Format Online-Ressource, XVIII, 239 p. 1 illus. : online resource.
Andere Ausgabe(n) Printed edition:: ISBN: 978-3-031-52644-2
Printed edition:: ISBN: 978-3-031-52646-6
Printed edition:: ISBN: 978-3-031-52647-3
Inhalt Part I Why Big Data Is Not Smart Yet? -- 1. Introduction -- 2. Why Do Big Data and Machine Learning Entail the Fractional Dynamics? -- Part II Smart Big Data Acquisition Platforms -- 3. Small Unmanned Aerial Vehicles (UAVs) and Remote Sensing Payloads -- 4. The Edge-AI Sensors and Internet of Living Things (IoLT) -- 5. The Unmanned Ground Vehicles (UGVs) for Digital Agriculture -- Part III Advanced Big Data Analytics, Plant Physiology-informed Machine Learning, and Fractional-order Thinking -- 6. Fundamentals of Big Data, Machine Learning, and Computer VisionWorkflow -- 7. A Low-cost Proximate Sensing Method for Early Detection of Nematodes inWalnut Using Machine Learning Algorithms -- 8. Tree-level Evapotranspiration Estimation of Pomegranate Trees Using Lysimeter and UAV Multispectral Imagery -- 9. Individual Tree-level Water Status Inference Using High-resolution UAV Thermal Imagery and Complexity-informed Machine Learning -- 10. Scale-aware Pomegranate Yield Prediction Using UAV Imagery and Machine Learning -- Part IV Towards Smart Big Data in Digital Agriculture -- 11. Intelligent Bugs Mapping and Wiping (iBMW): An Affordable Robot-Driven Robot for Farmers -- 12. A Non-invasive Stem Water Potential Monitoring Method Using Proximate Sensor and Machine Learning Classification Algorithms -- 13. A Low-cost Soil Moisture Monitoring Method by Using Walabot and Machine Learning Algorithms -- 14. Conclusions and Future Research
Persistent Identifier URN: urn:nbn:de:101:1-2024022903091791045505
DOI: 10.1007/978-3-031-52645-9
URL https://doi.org/10.1007/978-3-031-52645-9
ISBN/Einband/Preis 978-3-031-52645-9
Sprache(n) Englisch (eng)
Beziehungen Agriculture Automation and Control
DDC-Notation 630.2 (maschinell ermittelte DDC-Kurznotation)
Sachgruppe(n) 630 Landwirtschaft, Veterinärmedizin

Online-Zugriff Archivobjekt öffnen




Treffer 5 von 99
< < > <


E-Mail-IconAdministration