4.3 Article

Computer Vision and Deep Learning-enabled Weed Detection Model for Precision Agriculture

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Agronomy

Early Weed Detection Using Image Processing and Machine Learning Techniques in an Australian Chilli Farm

Nahina Islam et al.

Summary: This paper explores the potential of machine learning algorithms for weed and crop classification from UAV images, with random forest and SVM algorithms identified as efficient and practical for weed detection.

AGRICULTURE-BASEL (2021)

Review Chemistry, Analytical

Review of Weed Detection Methods Based on Computer Vision

Zhangnan Wu et al.

Summary: This review elaborates on the solutions to weed detection problems using traditional image-processing methods and deep learning-based methods, providing an overview of various methods, advantages and disadvantages, as well as introducing related datasets and machinery. It also analyzes the problems and difficulties of existing weed detection methods and prospects the future research trends.

SENSORS (2021)

Article Agriculture, Multidisciplinary

Graph weeds net: A graph-based deep learning method for weed recognition

Kun Hu et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2020)

Article Environmental Sciences

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

Arun Narenthiran Veeranampalayam Sivakumar et al.

REMOTE SENSING (2020)

Article Agronomy

Paddy Crop and Weed Discrimination: A Multiple Classifier System Approach

Radhika Kamath et al.

INTERNATIONAL JOURNAL OF AGRONOMY (2020)

Article Multidisciplinary Sciences

Dataset of annotated food crops and weed images for robotic computer vision control

Kaspars Sudars et al.

DATA IN BRIEF (2020)

Review Agriculture, Multidisciplinary

A review on weed detection using ground-based machine vision and image processing techniques

Aichen Wang et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2019)

Article Agronomy

Deep learning for image-based weed detection in turfgrass

Jialin Yu et al.

EUROPEAN JOURNAL OF AGRONOMY (2019)

Article Plant Sciences

Weed Detection in Perennial Ryegrass With Deep Learning Convolutional Neural Network

Jialin Yu et al.

FRONTIERS IN PLANT SCIENCE (2019)

Article Computer Science, Artificial Intelligence

Farmland fertility: A new metaheuristic algorithm for solving continuous optimization problems

Human Shayanfar et al.

APPLIED SOFT COMPUTING (2018)

Article Agriculture, Multidisciplinary

Evaluation of support vector machine and artificial neural networks in weed detection using shape features

Adel Bakhshipour et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Review Agriculture, Multidisciplinary

Deep learning in agriculture: A survey

Andreas Kamilaris et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2018)

Article Engineering, Electrical & Electronic

Small Object Detection with Multiscale Features

Guo X. Hu et al.

INTERNATIONAL JOURNAL OF DIGITAL MULTIMEDIA BROADCASTING (2018)

Article Agriculture, Multidisciplinary

Weed detection in soybean crops using ConvNets

Alessandro dos Santos Ferreira et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2017)

Article Agriculture, Multidisciplinary

Aquatic weed automatic classification using machine learning techniques

Luis A. M. Pereira et al.

COMPUTERS AND ELECTRONICS IN AGRICULTURE (2012)

Article Computer Science, Artificial Intelligence

Extreme learning machine: Theory and applications

Guang-Bin Huang et al.

NEUROCOMPUTING (2006)

Article Acoustics

New insights into the noise reduction Wiener filter

Jingdong Chen et al.

IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2006)