A High-Level Survey of Optical Remote Sensing
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917282214576128 |
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| author | Koletsis, Panagiotis Efthymiou, Vasilis Vakalopoulou, Maria Komodakis, Nikos Doulamis, Anastasios Papadopoulos, Georgios Th. |
| author_facet | Koletsis, Panagiotis Efthymiou, Vasilis Vakalopoulou, Maria Komodakis, Nikos Doulamis, Anastasios Papadopoulos, Georgios Th. |
| contents | In recent years, significant advances in computer vision have also propelled progress in remote sensing. Concurrently, the use of drones has expanded, with many organizations incorporating them into their operations. Most drones are equipped by default with RGB cameras, which are both robust and among the easiest sensors to use and interpret. The body of literature on optical remote sensing is vast, encompassing diverse tasks, capabilities, and methodologies. Each task or methodology could warrant a dedicated survey. This work provides a comprehensive overview of the capabilities of the field, while also presenting key information, such as datasets and insights. It aims to serve as a guide for researchers entering the field, offering high-level insights and helping them focus on areas most relevant to their interests. To the best of our knowledge, no existing survey addresses this holistic perspective. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_17397 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A High-Level Survey of Optical Remote Sensing Koletsis, Panagiotis Efthymiou, Vasilis Vakalopoulou, Maria Komodakis, Nikos Doulamis, Anastasios Papadopoulos, Georgios Th. Computer Vision and Pattern Recognition Artificial Intelligence In recent years, significant advances in computer vision have also propelled progress in remote sensing. Concurrently, the use of drones has expanded, with many organizations incorporating them into their operations. Most drones are equipped by default with RGB cameras, which are both robust and among the easiest sensors to use and interpret. The body of literature on optical remote sensing is vast, encompassing diverse tasks, capabilities, and methodologies. Each task or methodology could warrant a dedicated survey. This work provides a comprehensive overview of the capabilities of the field, while also presenting key information, such as datasets and insights. It aims to serve as a guide for researchers entering the field, offering high-level insights and helping them focus on areas most relevant to their interests. To the best of our knowledge, no existing survey addresses this holistic perspective. |
| title | A High-Level Survey of Optical Remote Sensing |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2602.17397 |