Abstract
Weed identification is a fundamental step in weed management. Traditional identification based on taxonomic features can be extremely challenging, especially at young seedling stage. It could also take days or months to confirm the identification through various channels, which would mean the loss of prime opportunity to control the weed. Recent advances in computer vision and machine learning have shown great success in various automatic visual detection tasks. It is therefore appropriate choice to capture visual field information and further process it to be able to realize autonomous weed identification promptly. This paper presents a convenient approach that applies image processing and machine learning for quick and accurate weeds identification on-site. Three deep models have been implemented to identify weeds via a smartphone. It is a proof-of-concept study targeting 16 selected most important agricultural weeds in Australia. We believe the proposed approach can help growers make a timely decision to spray the corresponding herbicide to reduce the financial loss annually.
Original language | English |
---|---|
Title of host publication | Image and Video Technology |
Subtitle of host publication | 10th Pacific-Rim Symposium, PSIVT 2022, Bintan Island, Indonesia, November 12–14, 2022, Proceedings |
Publisher | Springer |
Pages | 146-158 |
Number of pages | 13 |
Volume | 13763 |
ISBN (Electronic) | 9783031264313 |
ISBN (Print) | 9783031264306 |
DOIs | |
Publication status | Published - 28 Apr 2023 |
Event | 10th Pacific-Rim Symposium on Image and Video Technology: PSIVT 2022 - Online Duration: 25 Nov 2022 → 28 Nov 2022 http://www.cis-ram.org/psivt2022/workshops.html (Conference website) http://www.cis-ram.org/psivt2022/call_for_papers.html (Call for papers) http://www.cis-ram.org/psivt2022/program.html (Program) https://arc.nus.edu.sg/wordpress/wp-content/uploads/2022/05/PSIVT-c4p-revised-v8_1.pdf https://link.springer.com/book/9783031264320 (Proceedings due for publication April 2023 - SpringerLink) |
Publication series
Name | Lecture Notes in Computer Sciences |
---|---|
Publisher | Springer |
Volume | 13763 |
ISSN (Print) | 0302-9743 |
Conference
Conference | 10th Pacific-Rim Symposium on Image and Video Technology |
---|---|
Period | 25/11/22 → 28/11/22 |
Other | The Pacific-Rim Symposium on Image and Video Technology (PSIVT) is a premier level biennial series of symposia that aim at providing a forum for researchers and practitioners who are being involving, or are contributing to theoretical advances or practical implementations in image and video technology. The 10-th Pacific-Rim Symposium on Image and Video Technology (PSIVT 2022) will be held Online from 25th to 28th November, 2022. The PSIVT is a premier level biennial series of symposia that aims to provide a forum for researchers and practitioners in the Pacific Rim and around the world who are involving in contributing to theoretical advances or practical implementations in image and video technology. The PSIVT has been held 9 times. It is a highly referenced conference that provides authors with useful feedbacks. Submissions are invited on significant, original, and previously unpublished research on all aspects of image and video technology. All papers will receive mindful and rigorous reviews. |
Internet address |
|