fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf
fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf
fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf
fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf
fachmedien.de - spezialisierte Fachinformationen für Studium und Beruf

Site Breadcrumb

Verkauf durch Sack Fachmedien

Bacanin / Chhabra / Kour

Plant Disease Detection Using Machine Learning, Deep Learning, and Metaheuristics

Medium: Buch
ISBN: 978-1-041-28977-7
Verlag: Taylor & Francis Ltd
Erscheinungstermin: 03.11.2026
Jetzt vorbestellen
vorbestellbar, Erscheinungstermin ca. November 2026
Auf die Merkliste Drucken
Überschrift

Beschreibung

Kostenloser Versand

nach Deutschland, Österreich und in die Schweiz

Bequem zahlen

Rechnung, Kreditkarte, PayPal oder Bankeinzug

Wir sind gerne für Sie da

0800 000-1378 (Inland)
service@fachmedien.de
<<Kontaktformular>>

Fragen

Fragen Lorem ipsum dolor sit amet, consetetur sadipscing elitr, sed diam nonumy eirmod tempor invidunt ut labore et dolore magna aliquyam erat, sed diam voluptua
Anwtorten

Anwtorten At vero eos et accusam et justo duo dolores et ea rebum. Stet clita kasd gubergren, no sea takimata sanctus est Lorem ipsum dolor sit amet. Lorem ipsum dolor sit amet

The book explores how machine learning (ML), deep learning (DL), and metaheuristic optimization techniques can revolutionize plant disease detection and agricultural intelligence. Unlike traditional agronomic approaches, this book bridges advanced computational methods with real-world agricultural needs. It emphasizes both the scientific and practical dimensions—focusing on image-based disease detection, sensor data interpretation, optimization of predictive models, and real-world deployment strategies. The book looks at the subject from a technology, biological & agricultural, computational optimization, practical and social impact perspective.

This edited book is designed for researchers, academicians, and professionals working in Artificial Intelligence, Machine Learning, Deep Learning, Metaheuristics, and agricultural sciences. It will also benefit agricultural engineers, data scientists, agritech industries, policymakers, and undergraduate, postgraduate, and doctoral students interested in AI-driven plant disease detection and smart agriculture applications.

Produkteigenschaften

Themen

Autoren/Hrsg.

Herausgeber

Preface. 1. Introduction to Plant Disease Detection in Agriculture. 2. Machine Learning for Agricultural Application. 3. Advancing Mango Leaf Disease Detection Through Deep Learning: YOLOv11 Versus YOLOv12. 4. Metaheuristics and Optimization in Agricultural AI: Advancing Plant Disease Detection and Smart Farming. 5. Data Acquisition and Preprocessing for Plant Disease Detection. 6. Machine Learning for Disease Classification and Prediction. 7. Deep Learning Architectures for Image-Based Plant Disease Analysis. 8. Hybrid Models: Integrating ML, DL, and Metaheuristics. 9. Stage-Wise Attention-Guided CNN (2S-XAI-CNN) for High-Accuracy Rice Leaf Disease Classification. 10. Limitations and Challenges of Artificial Intelligence in Crop Disease Detection. 11. Economic Environment Impact of AI and Machine Learning in Plant Disease Detection and Sustainable Agriculture. 12. Emerging Trends and Innovations. 13. Roadmap for the Future Research. 14. Future Prospects of Plant Disease Detection in Sustainable Agriculture.