Computer Vision And Machine Learning In Agriculture

Download Computer Vision And Machine Learning In Agriculture full books in PDF, epub, and Kindle. Read online free Computer Vision And Machine Learning In Agriculture ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Computer Vision and Machine Learning in Agriculture

Computer Vision and Machine Learning in Agriculture
Author :
Publisher : Springer Nature
Total Pages : 172
Release :
ISBN-10 : 9789813364240
ISBN-13 : 9813364246
Rating : 4/5 (246 Downloads)

Book Synopsis Computer Vision and Machine Learning in Agriculture by : Mohammad Shorif Uddin

Download or read book Computer Vision and Machine Learning in Agriculture written by Mohammad Shorif Uddin and published by Springer Nature. This book was released on 2021-03-23 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Computer Vision and Machine Learning in Agriculture Related Books

Computer Vision and Machine Learning in Agriculture
Language: en
Pages: 172
Authors: Mohammad Shorif Uddin
Categories: Technology & Engineering
Type: BOOK - Published: 2021-03-23 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for autom
Computer Vision and Machine Learning in Agriculture, Volume 2
Language: en
Pages: 269
Authors: Mohammad Shorif Uddin
Categories: Technology & Engineering
Type: BOOK - Published: 2022-03-13 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture” for academicians, researchers, and professionals interes
Artificial Intelligence in Agriculture
Language: en
Pages: 186
Authors: Rajesh Singh
Categories: Technology & Engineering
Type: BOOK - Published: 2021-11-23 - Publisher: CRC Press

DOWNLOAD EBOOK

This book is a platform for anyone who wishes to explore Artificial Intelligence in the field of agriculture from scratch or broaden their understanding and its
Computer Vision-Based Agriculture Engineering
Language: en
Pages: 379
Authors: Han Zhongzhi
Categories: Science
Type: BOOK - Published: 2019-09-16 - Publisher: CRC Press

DOWNLOAD EBOOK

In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safe
Data Science in Agriculture and Natural Resource Management
Language: en
Pages: 326
Authors: G. P. Obi Reddy
Categories: Technology & Engineering
Type: BOOK - Published: 2021-10-11 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science