为何获胜者是最佳？
计算机视觉与模式识别
2023-04-03 v1 机器学习
摘要
国际基准竞赛已成为图像分析方法比较性能评估的基础。然而，极少有研究关注从这些竞赛中能学到什么。它们真的产生了科学进展吗？常见且成功的参与策略是什么？是什么使一个解决方案优于竞争方法？为弥补文献中的这一空白，我们对IEEE ISBI 2021和MICCAI 2021范围内的全部80项竞赛进行了多中心研究。基于提交的算法及其排名的全面描述，以及潜在的参与策略所做的统计分析，揭示了获胜方案的共性特征。这些特征通常包括使用多任务学习（63%）和/或多阶段流水线（61%），以及关注增强（100%）、图像预处理（97%）、数据整理（79%）和后处理（66%）。获胜团队的典型负责人是拥有博士学位的计算机科学家，具有五年生物医学图像分析经验和四年深度学习经验。对于排名靠前的团队，两种核心通用开发策略尤为突出：在方法设计中体现度量指标，以及专注于分析并处理失败案例。据组织者称，43%的获胜算法超越了最先进水平(state of the art)，但仅11%完全解决了相应领域问题。我们研究的见解可帮助研究人员（1）在应对新问题时改进算法开发策略，以及（2）聚焦于本工作所揭示的开放研究问题。
引用
@article{arxiv.2303.17719,
title = {Why is the winner the best?},
author = {Matthias Eisenmann and Annika Reinke and Vivienn Weru and Minu Dietlinde Tizabi and Fabian Isensee and Tim J. Adler and Sharib Ali and Vincent Andrearczyk and Marc Aubreville and Ujjwal Baid and Spyridon Bakas and Niranjan Balu and Sophia Bano and Jorge Bernal and Sebastian Bodenstedt and Alessandro Casella and Veronika Cheplygina and Marie Daum and Marleen de Bruijne and Adrien Depeursinge and Reuben Dorent and Jan Egger and David G. Ellis and Sandy Engelhardt and Melanie Ganz and Noha Ghatwary and Gabriel Girard and Patrick Godau and Anubha Gupta and Lasse Hansen and Kanako Harada and Mattias Heinrich and Nicholas Heller and Alessa Hering and Arnaud Huaulmé and Pierre Jannin and Ali Emre Kavur and Oldřich Kodym and Michal Kozubek and Jianning Li and Hongwei Li and Jun Ma and Carlos Martín-Isla and Bjoern Menze and Alison Noble and Valentin Oreiller and Nicolas Padoy and Sarthak Pati and Kelly Payette and Tim Rädsch and Jonathan Rafael-Patiño and Vivek Singh Bawa and Stefanie Speidel and Carole H. Sudre and Kimberlin van Wijnen and Martin Wagner and Donglai Wei and Amine Yamlahi and Moi Hoon Yap and Chun Yuan and Maximilian Zenk and Aneeq Zia and David Zimmerer and Dogu Baran Aydogan and Binod Bhattarai and Louise Bloch and Raphael Brüngel and Jihoon Cho and Chanyeol Choi and Qi Dou and Ivan Ezhov and Christoph M. Friedrich and Clifton Fuller and Rebati Raman Gaire and Adrian Galdran and Álvaro García Faura and Maria Grammatikopoulou and SeulGi Hong and Mostafa Jahanifar and Ikbeom Jang and Abdolrahim Kadkhodamohammadi and Inha Kang and Florian Kofler and Satoshi Kondo and Hugo Kuijf and Mingxing Li and Minh Huan Luu and Tomaž Martinčič and Pedro Morais and Mohamed A. Naser and Bruno Oliveira and David Owen and Subeen Pang and Jinah Park and Sung-Hong Park and Szymon Płotka and Elodie Puybareau and Nasir Rajpoot and Kanghyun Ryu and Numan Saeed and Adam Shephard and Pengcheng Shi and Dejan Štepec and Ronast Subedi and Guillaume Tochon and Helena R. Torres and Helene Urien and João L. Vilaça and Kareem Abdul Wahid and Haojie Wang and Jiacheng Wang and Liansheng Wang and Xiyue Wang and Benedikt Wiestler and Marek Wodzinski and Fangfang Xia and Juanying Xie and Zhiwei Xiong and Sen Yang and Yanwu Yang and Zixuan Zhao and Klaus Maier-Hein and Paul F. Jäger and Annette Kopp-Schneider and Lena Maier-Hein},
journal= {arXiv preprint arXiv:2303.17719},
year = {2023}
}
备注
accepted to CVPR 2023