Mohlo by se vám také líbit

Více informací o knize Computer Vision and Machine Learning in Agriculture

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 539 bodů

Anotace knihy

This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for automatic visual understanding and recognition which finds huge applications in agricultural productions. It also entails how rendering of machine learning techniques to computer vision algorithms is boosting this sector with better productivity by developing more precise systems. Computer vision and machine learning (CV-ML) helps in plant disease assessment along with crop condition monitoring to control the degradation of yield, quality, and severe financial loss for farmers. Significant scientific and technological advances have been made in defect assessment, quality grading, disease recognition, pests, insects, fruits, and vegetable types recognition and evaluation of a wide range of agricultural plants, crops, leaves, and fruits. The book discusses intelligent robots developed with the touch of CV-ML which can help farmers to perform various tasks like planting, weeding, harvesting, plant health monitoring, and so on. The topics covered in the book include plant, leaf, and fruit disease detection, crop health monitoring, applications of robots in agriculture, precision farming, assessment of product quality and defects, pest, insect, fruits, and vegetable types recognition.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Computer Vision and Machine Learning in Agriculture
• Autor: Mohammad Shorif Uddin, Jagdish Chand Bansal
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 172
• EAN: 9789813364264
• ID: 38808282
• Nakladatelství: Springer Verlag, Singapore
• Hmotnost: 296 g
• Rozměry: 235 × 155 × 11 mm
• Datum vydání: 25. March 2022

Oblíbené z jiného soudku

---

---

---