Results 31 to 40 of about 1,584 (104)

Design and Experimental Evaluation of a Smart Intra-Row Weed Control System for Open-Field Cabbage

Agronomy
Addressing the challenges of complex structure, limited modularization capability, and insufficient responsiveness in traditional hydraulically driven inter-plant mechanical weeding equipment, this study designed and developed an electric swing-type ...
Shenyu Zheng, Xueguan Zhao, Hao Fu, Haoran Tan, Changyuan Zhai, Liping Chen   +5 more
doaj   +1 more source

Extraction of Citrus Trees from UAV Remote Sensing Imagery Using YOLOv5s and Coordinate Transformation

Remote Sensing, 2022
Obtaining the geographic coordinates of single fruit trees enables the variable rate application of agricultural production materials according to the growth differences of trees, which is of great significance to the precision management of citrus ...
Haoxin Tian, Xipeng Fang, Yubin Lan, Chenyang Ma, Huasheng Huang, Xiaoyang Lu, Dehua Zhao, Hanchao Liu, Yali Zhang   +8 more
doaj   +1 more source

Field Validation of a Laser-Based Robotic System for Autonomous Weed Control in Organic Farming

AgriEngineering
Weed management, particularly in organic farming, poses a significant challenge due to high manual labor costs and the crop’s low competitive ability. Precision laser technology offers a promising non-chemical alternative.
Vitali Czymmek, Jost Völckner, Felix Zilske, Stephan Hussmann   +3 more
doaj   +1 more source

Lightweight GSP-YOLO for accurate weed seedling detection and edge deployment in laser-based weed control systems

Smart Agricultural Technology
In precision agriculture, the integration of artificial intelligence with targeted weeding technologies provides critical support for efficient and accurate weed control.
Liu Saisai, Xie Qing, Tang Qing, Wu Jun, Jiang Lan, Guan Zhuohuai, Wu Chongyou   +6 more
doaj   +1 more source

Evaluation of Inference Performance of Deep Learning Models for Real-Time Weed Detection in an Embedded Computer

Sensors
The knowledge that precision weed control in agricultural fields can reduce waste and increase productivity has led to research into autonomous machines capable of detecting and removing weeds in real time.
Canicius Mwitta, Glen C. Rains, Eric Prostko   +2 more
doaj   +1 more source

Technical study on the efficiency and models of weed control methods using unmanned ground vehicles: A review

Artificial Intelligence in Agriculture
As precision agriculture evolves, unmanned ground vehicles (UGVs) have become an essential tool for improving weed management techniques, offering automated and targeted methods that obviously reduce the reliance on manual labor and blanket herbicide ...
Evans K. Wiafe, Kelvin Betitame, Billy G. Ram, Xin Sun   +3 more
doaj   +1 more source

Research on Weed Reverse Detection Methods Based on Improved You Only Look Once (YOLO) v8: Preliminary Results

Agronomy
The rapid and accurate detection of weeds is the prerequisite and foundation for precision weeding, automation, and intelligent field operations. Due to the wide variety of weeds in the field and their significant morphological differences, most existing
Hui Liu, Yushuo Hou, Jicheng Zhang, Ping Zheng, Shouyin Hou   +4 more
doaj   +1 more source

Key Technologies and Prospects of Laser Weeding Robots

智慧农业
[Significance]Grass damage in farmland seriously restricts the quality and yield of crop planting and production, and promotes the occurrence of pests and diseases. Weed control is a necessary measure for high yield and high quality of crops.
YU Zhongyi, WANG Hongyu, HE Xiongkui, ZHAO Lei, WANG Yuanyuan, SUN Hai   +5 more
doaj   +1 more source

Stem detection using YOLO11 and convexity defects of leaf shape in weed image

ROBOMECH Journal
Robotic weeding has been attracting attention to reduce the burden of weeding in agriculture. In weeding by a robot, it is required to detect weeds correctly.
Seito Takeuchi, Shuyan Liu, Shunsuke Komizunai, Taku Senoo, Atsushi Konno   +4 more
doaj   +1 more source

Development of a Detection System for Types of Weeds in Maize (Zea mays L.) under Greenhouse Conditions Using the YOLOv5 v7.0 Model

Agriculture
Corn (Zea mays L.) is one of the most important cereals worldwide. To maintain crop productivity, it is important to eliminate weeds that compete for nutrients and other resources. The eradication of these causes environmental problems through the use of
Oscar Leonardo García-Navarrete, Oscar Santamaria, Pablo Martín-Ramos, Miguel Ángel Valenzuela-Mahecha, Luis Manuel Navas-Gracia   +4 more
doaj   +1 more source