2017 Robotic Instrument Segmentation Challenge

18 Feb 2019Max AllanAlex ShvetsThomas KurmannZichen ZhangRahul DuggalYun-Hsuan SuNicola RiekeIro LainaNiveditha KalavakondaSebastian BodenstedtLuis HerreraWenqi LiVladimir IglovikovHuoling LuoJian YangDanail StoyanovLena Maier-HeinStefanie SpeidelMahdi Azizian

In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison. However, this type of approach has had limited translation to problems in robotic assisted surgery as this field has never established the same level of common datasets and benchmarking methods... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet