NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation

Autor:	Trotter, Cameron, Atkinson, Georgia, Sharpe, Matt, Richardson, Kirsten, McGough, A. Stephen, Wright, Nick, Burville, Ben, Berggren, Per
Rok vydání:	2020
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We introduce the Northumberland Dolphin Dataset 2020 (NDD20), a challenging image dataset annotated for both coarse and fine-grained instance segmentation and categorisation. This dataset, the first release of the NDD, was created in response to the rapid expansion of computer vision into conservation research and the production of field-deployable systems suited to extreme environmental conditions -- an area with few open source datasets. NDD20 contains a large collection of above and below water images of two different dolphin species for traditional coarse and fine-grained segmentation. All data contained in NDD20 was obtained via manual collection in the North Sea around the Northumberland coastline, UK. We present experimentation using standard deep learning network architecture trained using NDD20 and report baselines results. Comment: 5 pages, 6 figures, download link, submitted to FGVC7 Workshop @ CVPR20
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2005.13359 Zobrazit plný text záznamu View this record from Arxiv