Intelligent data mining and fusion systems in agriculture / Xanthoula-Eirini Pantazi, Dimitrios Moshou, Dionysis Bochtis.
| Author/creator | Pantazi, Xanthoula-Eirini |
| Other author | Moshou, Dimitrios. |
| Other author | Bochtis, Dionysis. |
| Format | Electronic |
| Publication Info | London, United Kingdom ; San Diego, CA ; Cambrige, MA ; Oxford, United Kingdom : Academic Press, an imprint of Elsevier, 2020. |
| Description | vii, 323 pages : illustrations ; 23 cm |
| Supplemental Content | Full text available from eBooks on EBSCOhost |
| Supplemental Content | Full text available from eBook - Agricultural, Biological, and Food Sciences 2019 |
| Subjects |
| Contents | Sensors in agriculture -- Artificial intelligence in agriculture -- Utilization of multisensors and data fusion in precision agriculture -- Tutorial I : Weed detection -- Tutorial II : Disease detection with fusion techniques -- Tutorial III : Disease and nutrient stress detection -- Tutorial IV : Leaf disease recognition -- Tutorial V : Yield prediction -- Tutorial VI : Postharvest phenotyping -- General overview of the proposed data mining and fusion techniques in agriculture |
| Abstract | "Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion with application in agriculture for the nondestructive testing of agricultural products and crop condition monitoring. These methods are related to the combination of sensors with artificial intelligence architectures in precision agriculture including neural and deep learning algorithms, bioinspired hierarchical neural maps, and novelty detection algorithms capable of detecting anomalies in different conditions. The introduction of intelligent machines, autonomous vehicles, innovative sensing, and actuating technologies, together with improved information and communication technologies, offers a novel approach to monitoring for ensuring production efficiency. Thus, traditional agricultural operations management methods have been enhanced with novel technologies that involve sensor fusion for crop protection, condition monitoring, quality determination, and yield prediction. Based on increased sustainability concerning production systems, Intelligent Data Mining and Fusion Systems in Agriculture offers advanced students and entry-level professionals involved in agricultural science and engineering, geo-information science, and computer science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features that are offered through advanced artificial intelligence algorithms that are capable of providing a better view for crop status, leading to the efficient crop management in agriculture."-- Page 4 of cover |
| Bibliography note | Includes bibliographical references and index. |
| Access restriction | Available only to authorized users. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2019956109 |
| ISBN | 9780128143919 (paperback) |
| ISBN | 0128143916 (paperback) |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | ✔ Available |