Results 41 to 50 of about 11,845 (152)

Crop-Weed Segmentation and Classification Using YOLOv8 Approach for Smart Farming

Journal of Studies in Science and Engineering
Accurately segmenting crop and weed images in agricultural fields is crucial for precision farming and effective weed management. This study introduces a new method that leverages the YOLOv8 object detection model for precise crop and weed segmentation ...
Sandip Sonawane, Nitin N. Patil
doaj   +1 more source

PMDNet: An Improved Object Detection Model for Wheat Field Weed

Agronomy
Efficient and accurate weed detection in wheat fields is critical for precision agriculture to optimize crop yield and minimize herbicide usage. The dataset for weed detection in wheat fields was created, encompassing 5967 images across eight well ...
Zhengyuan Qi, Jun Wang
doaj   +1 more source

Weakly Supervised Perennial Weed Detection in a Barley Field [PDF]

, 2023
Leon-Friedrich Thomas, Mikael Änäkkälä, Antti Lajunen   +2 more
openalex   +1 more source

Deep Learning Techniques for Weed Detection in Agricultural Environments: A Comprehensive Review

IEEE Access
Agriculture has been completely transformed by Deep Learning (DL) techniques, which allow for quick object localization and detection. However, because weeds and crops are similar in color, form, and texture, weed detection and categorization can be ...
Deepthi G Pai, Radhika Kamath, Mamatha Balachandra   +2 more
doaj   +1 more source

Eco-friendly weeding through precise detection of growing points via efficient multi-branch convolutional neural networks

, 2023
Dewa Made Sri Arsa, Talha Ilyas, Seok-Hwan Park, Okjae Won, Hyongsuk Kim   +4 more
openalex   +1 more source

Object-Level Benchmark for Deep Learning-Based Detection and Classification of Weed Species

, 2023
A S M Mahmudul Hasan, Dean Diepeveen, Hamid Laga, M. G. K. Jones, Ferdous Sohel   +4 more
openalex   +1 more source

MKD8: An Enhanced YOLOv8 Model for High-Precision Weed Detection

Agriculture
Weeds are an inevitable element in agricultural production, and their significant negative impacts on crop growth make weed detection a crucial task in precision agriculture.
Wenxuan Su, Wenzhong Yang, Jiajia Wang, Doudou Ren, Danny Chen   +4 more
doaj   +1 more source

Weed Detection in Images of Carrot Fields Based on Improved YOLO v4

, 2021
Boyu Ying, Yuancheng Xu, Shuai Zhang, Yinggang Shi, Li Liu   +4 more
openalex   +2 more sources

YOLOv7 for Weed Detection in Cotton Fields Using UAV Imagery

AgriEngineering
Weed detection is critical for precision agriculture, enabling targeted herbicide application to reduce costs and enhance crop health. This study utilized UAV-acquired RGB imagery from cotton fields to develop and evaluate deep learning models for weed ...
Anindita Das, Yong Yang, Vinitha Hannah Subburaj   +2 more
doaj   +1 more source

Weed detection by using image processing

, 2023
Vijaykumar Bidve, Sulakshana B. Mane, Pradip K. Tamkhade, Ganesh Pakle   +3 more
openalex   +2 more sources