Enhancing species video detection capabilities at the obsea observatory through the integration of emuas cameras within the aneris project framework
High-resolution images captured by EMUAS cameras, equipped with a 4K sensor and set to 1440p resolution for the OBSEA deployment, are analysed using the YOLO (You Only Look Once) object detection algorithm, trained with labelled datasets from OBSEA. The cameras operate at 20 frames per second (fps)...
| Autores: | , , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/452096 |
| Acceso en línea: | https://hdl.handle.net/2117/452096 https://dx.doi.org/10.5821/iwp.2025.24.13985 |
| Access Level: | acceso abierto |
| Palabra clave: | Oceanography -- Research Oceanography -- Equipment and supplies Digital cameras High-resolution cameras EMUAS Biofouling UV-C AI algorithms YOLO Object detection Oceanografia -- Investigació Oceanografia -- Aparells i instruments Càmeres fotogràfiques digitals Àrees temàtiques de la UPC::Enginyeria civil::Geologia::Oceanografia Àrees temàtiques de la UPC::Enginyeria electrònica::Instrumentació i mesura Àrees temàtiques de la UPC::So, imatge i multimèdia::Dispositius de so, imatge i multimèdia |
| Sumario: | High-resolution images captured by EMUAS cameras, equipped with a 4K sensor and set to 1440p resolution for the OBSEA deployment, are analysed using the YOLO (You Only Look Once) object detection algorithm, trained with labelled datasets from OBSEA. The cameras operate at 20 frames per second (fps) with H.264+ encoding and a maximum bitrate of 16384. The machine learning model used efficiently identifies and classifies up to 24 marine species. By leveraging convolutional neural networks, the system provides accurate and real-time species recognition, supporting biodiversity assessments and facilitating data-driven marine conservation efforts. |
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