COT-AD: Cotton Analysis Dataset
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arXiv
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| Format: | Preprint |
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2025
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| author | Ali, Akbar Vyas, Mahek Debnath, Soumyaratna Kamra, Chanda Grover Khalane, Jaidev Sanjay Devanesan, Reuben Shibu Mastan, Indra Deep Sankaranarayanan, Subramanian Khanna, Pankaj Raman, Shanmuganathan |
| author_facet | Ali, Akbar Vyas, Mahek Debnath, Soumyaratna Kamra, Chanda Grover Khalane, Jaidev Sanjay Devanesan, Reuben Shibu Mastan, Indra Deep Sankaranarayanan, Subramanian Khanna, Pankaj Raman, Shanmuganathan |
| contents | This paper presents COT-AD, a comprehensive Dataset designed to enhance cotton crop analysis through computer vision. Comprising over 25,000 images captured throughout the cotton growth cycle, with 5,000 annotated images, COT-AD includes aerial imagery for field-scale detection and segmentation and high-resolution DSLR images documenting key diseases. The annotations cover pest and disease recognition, vegetation, and weed analysis, addressing a critical gap in cotton-specific agricultural datasets. COT-AD supports tasks such as classification, segmentation, image restoration, enhancement, deep generative model-based cotton crop synthesis, and early disease management, advancing data-driven crop management |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_18532 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | COT-AD: Cotton Analysis Dataset Ali, Akbar Vyas, Mahek Debnath, Soumyaratna Kamra, Chanda Grover Khalane, Jaidev Sanjay Devanesan, Reuben Shibu Mastan, Indra Deep Sankaranarayanan, Subramanian Khanna, Pankaj Raman, Shanmuganathan Computer Vision and Pattern Recognition I.4.9; I.5.4; H.2.8 This paper presents COT-AD, a comprehensive Dataset designed to enhance cotton crop analysis through computer vision. Comprising over 25,000 images captured throughout the cotton growth cycle, with 5,000 annotated images, COT-AD includes aerial imagery for field-scale detection and segmentation and high-resolution DSLR images documenting key diseases. The annotations cover pest and disease recognition, vegetation, and weed analysis, addressing a critical gap in cotton-specific agricultural datasets. COT-AD supports tasks such as classification, segmentation, image restoration, enhancement, deep generative model-based cotton crop synthesis, and early disease management, advancing data-driven crop management |
| title | COT-AD: Cotton Analysis Dataset |
| topic | Computer Vision and Pattern Recognition I.4.9; I.5.4; H.2.8 |
| url | https://arxiv.org/abs/2507.18532 |