Results 61 to 70 of about 11,448 (161)

Enhancing rangeland weed detection through convolutional neural networks and transfer learning

Crop Design
The detection of weed species in rangeland environments is a challenging task due to various factors such as dense, variable species vegetation, ocular occlusion, and a wide variety of plant morphology.
Christian Shackleton, Raja Hashim Ali, Talha Ali Khan   +2 more
doaj   +1 more source

Examining Difficulties in Weed Detection

, 2022
Automatic detection of weeds could be used for more efficient weed control in agriculture. In this master thesis, weed detectors have been trained and examined on data collected by RISE to investigate whether an accurate weed detector could be trained on the collected data. When only using annotations of the weed class Creeping thistle for training and
openaire   +1 more source

Remote Aerial Vehicle Solutions for Weed Detection in Precision Agriculture

IEEE Access
This study presents a novel Remote Aerial Vehicle-based approach for detecting pigweeds in soybean (Glycine max) fields using a combination of deep learning and advanced image processing techniques.
Shekhar S. Borah, Aryan Anand, Prabha Sundaravadivel, Reginald Fletcher, Krishna N. Reddy   +4 more
doaj   +1 more source

TARGET DETECTION FOR WEEDING ROBOTS BASED ON IMPROVED YOLOv11 MODELS

Engenharia Agrícola
This paper addresses the issues of insufficient accuracy and energy efficiency balance in the weed detection models that are currently used in agricultural weeding robots. To tackle this problem, we propose an enhanced YOLOv11-SNEW algorithm based on the
Jianguo Meng, Yanzhou Li, Zhipeng Li, Wenxia Xie   +3 more
doaj   +1 more source

Key Technologies of Intelligent Weeding for Vegetables: A Review

Agriculture
Vegetables are an essential part of people’s daily diet, and weeds can cause serious losses in vegetable yield and quality. Intelligent weeding technology for vegetables will be one of the mainstream technologies in modern agricultural development.
Jinkang Jiao, Ying Zang, Chaowen Chen
doaj   +1 more source

Advancing precision agriculture: A comparative analysis of YOLOv8 for multi-class weed detection in cotton cultivation

Artificial Intelligence in Agriculture
Effective weed management plays a critical role in enhancing the productivity and sustainability of cotton cultivation. The rapid emergence of herbicide-resistant weeds has underscored the need for innovative solutions to address the challenges ...
Ameer Tamoor Khan, Signe Marie Jensen, Abdul Rehman Khan   +2 more
doaj   +1 more source

Weed Detection by Aerial Imagery

, 2020
Dans le contexte agricole actuel, il est nécessaire de réduire l’utilisation des produits phytosanitaires contre les mauvaises herbes. Le désherbage localisé présente une alternative prometteuse pour limiter les coûts et l’impact environnemental.
openaire   +1 more source

Weed detection in soybean fields using improved YOLOv7 and evaluating herbicide reduction efficacy. [PDF]

Front Plant Sci, 2023
Li J, Zhang W, Zhou H, Yu C, Li Q.
europepmc   +1 more source

Detection of weeds in vegetables using image classification neural networks and image processing

Frontiers in Physics
Weed management presents a major challenge to vegetable growth. Accurate identification of weeds is essential for automated weeding. However, the wide variety of weed types and their complex distribution creates difficulties in rapid and accurate weed ...
Huiping Jin, Kang Han, Kang Han, Hongting Xia, Bo Xu, Xiaojun Jin   +5 more
doaj   +1 more source

Weed detection and/or destruction

, 2009
A method of determining the position of weeds growing in soil amongst crops comprising the steps of:- Using a camera to acquiring a stereoscopic image of plants growing on soil; - Segmentation plant pixels and soil pixels; - Creating a modelised height profile of the soil at positions at which soil pixels have not been captured by the stereoscopic ...
Piron, Alexis, Destain, Marie-France
openaire   +1 more source