Results 21 to 30 of about 11,845 (152)

The Application of Hyperspectral Remote Sensing Imagery (HRSI) for Weed Detection Analysis in Rice Fields: A Review

Applied Sciences, 2022
Weeds are found on every cropland across the world. Weeds compete for light, water, and nutrients with attractive plants, introduce illnesses or viruses, and attract harmful insects and pests, resulting in yield loss. New weed detection technologies have
Nursyazyla Sulaiman, Nik Norasma Che’Ya, Muhammad Huzaifah Mohd Roslim, Abdul Shukor Juraimi, Nisfariza Mohd Noor, Wan Fazilah Fazlil Ilahi   +5 more
doaj   +1 more source

Comparison of Object Detection and Patch-Based Classification Deep Learning Models on Mid- to Late-Season Weed Detection in UAV Imagery

Remote Sensing, 2020
Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons.
Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi   +6 more
doaj   +1 more source

Modified Barnacles Mating Optimization with Deep Learning Based Weed Detection Model for Smart Agriculture

Applied Sciences, 2022
Weed control is a significant means to enhance crop production. Weeds are accountable for 45% of the agriculture sector’s crop losses, which primarily occur because of competition with crops. Accurate and rapid weed detection in agricultural fields was a
Amani Abdulrahman Albraikan, Mohammed Aljebreen, Jaber S. Alzahrani, Mahmoud Othman, Gouse Pasha Mohammed, Mohamed Ibrahim Alsaid   +5 more
doaj   +1 more source

Weed detection in agricultural fields using machine vision [PDF]

BIO Web of Conferences
Weeds have the potential to cause significant damage to agricultural fields, so the development of weed detection and automatic weed control in these areas is very important.
Moldvai László, Ambrus Bálint, Teschner Gergely, Nyéki Anikó   +3 more
doaj   +1 more source

Deep Object Detection of Crop Weeds: Performance of YOLOv7 on a Real Case Dataset from UAV Images

Remote Sensing, 2023
Weeds are a crucial threat to agriculture, and in order to preserve crop productivity, spreading agrochemicals is a common practice with a potential negative impact on the environment.
Ignazio Gallo, Anwar Ur Rehman, Ramin Heidarian Dehkordi, Nicola Landro, Riccardo La Grassa, Mirco Boschetti   +5 more
doaj   +1 more source

Weed Density Detection Method Based on Absolute Feature Corner Points in Field

Agronomy, 2020
Field weeds identification is challenging for precision spraying, i.e., the automation identification of the weeds from the crops. For rapidly obtaining weed distribution in field, this study developed a weed density detection method based on absolute ...
Yanlei Xu, Run He, Zongmei Gao, Chenxiao Li, Yuting Zhai, Yubin Jiao   +5 more
doaj   +1 more source

Weed Detection Method Based on Lightweight and Contextual Information Fusion

Applied Sciences, 2023
Weed detection technology is of paramount significance in achieving automation and intelligence in weed control. Nevertheless, it grapples with several formidable challenges, including imprecise small target detection, high computational demands ...
Chi Zhang, Jincan Liu, Hongjun Li, Haodong Chen, Zhangxun Xu, Zhen Ou   +5 more
doaj   +1 more source

Early Detection of Broad-Leaved and Grass Weeds in Wide Row Crops Using Artificial Neural Networks and UAV Imagery

Agronomy, 2021
Significant advances in weed mapping from unmanned aerial platforms have been achieved in recent years. The detection of weed location has made possible the generation of site specific weed treatments to reduce the use of herbicides according to weed ...
Jorge Torres-Sánchez, Francisco Javier Mesas-Carrascosa, Francisco M. Jiménez-Brenes, Ana I. de Castro, Francisca López-Granados   +4 more
doaj   +1 more source

Weed Detection Algorithms in Rice Fields Based on Improved YOLOv10n

Agriculture
Weeds in paddy fields compete with rice for nutrients and cause pests and diseases, greatly affecting rice yield. Accurate weed detection is vital for implementing variable spraying with unmanned aerial vehicles (UAV) for weed control.
Yan Li, Zhonghui Guo, Yan Sun, Xiaoan Chen, Yingli Cao   +4 more
doaj   +1 more source

Weed25: A deep learning dataset for weed identification

Frontiers in Plant Science, 2022
Weed suppression is an important factor affecting crop yields. Precise identification of weed species will contribute to automatic weeding by applying proper herbicides, hoeing position determination, and hoeing depth to specific plants as well as ...
Pei Wang, Pei Wang, Pei Wang, Yin Tang, Fan Luo, Lihong Wang, Chengsong Li, Qi Niu, Hui Li, Hui Li   +9 more
doaj   +1 more source