Towards Varroa destructor mite detection using a narrow spectra illumination
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912316503621632 |
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| author | Bielik, Samuel Bilik, Simon |
| author_facet | Bielik, Samuel Bilik, Simon |
| contents | This paper focuses on the development and modification of a beehive monitoring device and Varroa destructor detection on the bees with the help of hyperspectral imagery while utilizing a U-net, semantic segmentation architecture, and conventional computer vision methods. The main objectives were to collect a dataset of bees and mites, and propose the computer vision model which can achieve the detection between bees and mites. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_06099 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Varroa destructor mite detection using a narrow spectra illumination Bielik, Samuel Bilik, Simon Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning This paper focuses on the development and modification of a beehive monitoring device and Varroa destructor detection on the bees with the help of hyperspectral imagery while utilizing a U-net, semantic segmentation architecture, and conventional computer vision methods. The main objectives were to collect a dataset of bees and mites, and propose the computer vision model which can achieve the detection between bees and mites. |
| title | Towards Varroa destructor mite detection using a narrow spectra illumination |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2504.06099 |