Image-based Weed Classification
Image-Based Weed Classification is a computational method that identifies and categorizes pasture weed species through the analysis of visual features extracted from digital images, distinguishing itself from other classification approaches by relying primarily on pixel-level data and pattern recognition algorithms.
211
Publications
13.4K
Citations
689
Authors
272
Institutions
Publications per year
2017–2026
137
Parents
211
1–5 of 211
689
5
h-index
National University of Sciences and Technology, Pakistan
4 publications · 147 citations
5
h-index
5
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5
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National University of Sciences and Technology, Pakistan
4 publications · 147 citations
5
h-index
1–5 of 689
272

National University of Malaysia
Bangi, Malaysia
5 h-index
15 publications
756 citations
National University of Sciences and Technology
Islamabad, Pakistan
5 h-index
19 publications
588 citations

Nanjing Forestry University
Nanjing, China
5 h-index
10 publications
328 citations

Shiraz University
Shiraz, Iran
4 h-index
4 publications
182 citations

Aarhus University
Aarhus, Denmark
4 h-index
19 publications
798 citations
Centre for Automation and Robotics
Arganda, Spain
4 h-index
11 publications
1.4K citations

UNSW Sydney
Sydney, Australia
4 h-index
11 publications
507 citations
Technological University Dublin
Dublin, Ireland
4 h-index
3 publications
93 citations
1–8 of 272
21 publications · 2.6K citations
20
h-index
11 publications · 845 citations
11
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8 publications · 2.1K citations
8
h-index
7 publications · 389 citations
7
h-index
6 publications · 533 citations
7
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1–5