Buch, Englisch, 172 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 453 g
Buch, Englisch, 172 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 453 g
Reihe: Algorithms for Intelligent Systems
ISBN: 978-981-336-423-3
Verlag: Springer Nature Singapore
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
- Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Naturwissenschaften Agrarwissenschaften Agrarwissenschaften
Weitere Infos & Material
Chapter 1. Introduction to Computer Vision and Machine Learning Applications in Agriculture.- Chapter 2. Robots and Drones in Agriculture - A Survey.- Chapter 3. Detection of Rotten Fruits and Vegetables using Deep Learning.- Chapter 4. Deep Learning-Based Essential Paddy Pests Filtration Technique: A Better Economic Damage Management Process.- Chapter 5. Deep CNN-Based Mango Insect Classification.- Chapter 6. Implementation of a Deep Convolutional Neural Network for the Detection of Tomato Leaf Diseases.- Chapter 7. A Multi-Plant Disease Diagnosis Method using Convolutional Neural Network.- Chapter 8. A Deep Learning-Based Approach for Potato Diseases Classification.- Chapter 9. An In-Depth Analysis of Different Segmentation Techniques in Automated Local Fruit Disease Recognition.- Chapter 10. Machine Vision Based Fruit and Vegetable Disease Recognition: A Review.- Chapter 11. An Efficient Bag-of-Features for Diseased Plant Identification.