Robust Weed Classification
Robust Weed Classification is a methodological framework within vegetative weed identification that systematically enhances classification accuracy and consistency across diverse environmental conditions, plant growth stages, and imaging variations by integrating adaptive feature extraction, noise resilience, and generalizable decision rules.
9
Publications
852
Citations
48
Authors
15
Institutions
Publications per year
2017–2026
7
9
DeepWeeds: A Multiclass Weed Species Image Dataset for Deep Learning
Alex Olsen, Dmitry A. Konovalov, Bronson Philippa et al. · Scientific Reports · 2019 · 492 citations · Full text
A novel semi-supervised framework for UAV based crop/weed classification
Shahbaz Khan, Muhammad Tufail, Muhammad Tahir Khan et al. · PLoS ONE · 2021 · 63 citations · Full text
Weed seeds classification based on PCANet deep learning baseline
Xinshao Wang, Cai Cheng · 2015 · 62 citations
Olee Hoi Ying Lam, Marcel Dogotari, Moritz Prüm et al. · European Journal of Remote Sensing · 2020 · 58 citations · Full text
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15
National University of Sciences and Technology
Islamabad, Pakistan
2 h-index
6 publications
158 citations
Northwest A&F University
Yangling, China
1 h-index
2 publications
124 citations
University of Engineering and Technology Peshawar
Peshawar, Pakistan
1 h-index
5 publications
315 citations
University of Oxford
Oxford, United Kingdom
1 h-index
1 publications
31 citations
Fraunhofer-Gesellschaft
Munich, Germany
1 h-index
1 publications
31 citations
Rhine-Waal University of Applied Sciences
Kleve, Germany
1 h-index
6 publications
348 citations

University of Southern Denmark
Odense, Denmark
1 h-index
2 publications
50 citations
Lamarr Institute for Machine Learning and Artificial Intelligence
Sankt Augustin, Germany
1 h-index
1 publications
31 citations
1–8 of 15
1 publications · 31 citations
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1 publications · 19 citations
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1 publications · 56 citations
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1 publications · 63 citations
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1 publications · 492 citations
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