{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-ciona17-dataset-for-semantic-segmentation","title":"The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment","arxiv_id":"1702.05564","date":"2017-02-18","proceeding":null,"authors":["Angus Galloway","Graham W. Taylor","Aaron Ramsay","Medhat Moussa"],"abstract":"An original dataset for semantic segmentation, Ciona17, is introduced, which\nto the best of the authors' knowledge, is the first dataset of its kind with\npixel-level annotations pertaining to invasive species in a marine environment.\nDiverse outdoor illumination, a range of object shapes, colour, and severe\nocclusion provide a significant real world challenge for the computer vision\ncommunity. An accompanying ground-truthing tool for superpixel labeling, Truth\nand Crop, is also introduced. Finally, we provide a baseline using a variant of\nFully Convolutional Networks, and report results in terms of the standard mean\nintersection over union (mIoU) metric.","url_abs":"http://arxiv.org/abs/1702.05564v1","url_pdf":"http://arxiv.org/pdf/1702.05564v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"semantic-segmentation","task_name":"Semantic Segmentation"}],"methods":[],"datasets_introduced":[{"slug":"ciona17","name":"Ciona17","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1702.05564","atlas_url":"https://app.syntology.ai/?focus=1702.05564","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}