My Account Log in

1 option

Sensing Technologies for Field and In-House Crop Production : Technology Review and Case Studies / edited by Man Zhang, Han Li, Wenyi Sheng, Ruicheng Qiu, Zhao Zhang.

Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2023 Available online

View online
Format:
Book
Contributor:
Zhang, Man, editor.
Series:
Smart Agriculture, 2731-3484 ; 7
Language:
English
Subjects (All):
Robotics.
Mechatronics.
Agriculture.
Automation.
Image processing.
Robotic Engineering.
Image Processing.
Local Subjects:
Robotic Engineering.
Mechatronics.
Robotics.
Agriculture.
Automation.
Image Processing.
Physical Description:
1 online resource (144 pages)
Edition:
1st ed. 2023.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Summary:
This book focuses on state-of-the-art sensing and automation technologies for field crops and in-house product production and provides a lot of innovative knowledge on image processing, AI algorithms and applications in agriculture, and robotics. This book provides undergraduate or graduate students with take-away knowledge for unmanned agricultural production, including but not limited to corn disease detection, wheat head detection and counting, and soil nutrient condition monitoring. The first three chapters focus on reviewing plant phenotyping sensing technology and robotics and soil nutrient monitoring, followed by in-house crop sensing robotics. Then two case studies on corn and the other two case studies on wheat are presented.
Contents:
A Review of Three-Dimensional Multispectral Imaging in Plant Phenotyping
Recent Advances in Soil Nutrient Monitoring: A Review
Plant phenotyping robot platform
Autonomous crop image acquisition system based on ROS system
SeedingsNet: Field wheat seedling density detection based on deep learning
Wheat lodging detection using smart vision-based method
Design, construction, and experiment-based key parameter de-2 termination of auto maize seed placement system
Development and test of an auto seedling detection System.
Notes:
Includes bibliographical references.
Description based on publisher supplied metadata and other sources.
ISBN:
981-9979-27-7
OCLC:
1412622789

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account