no code implementations • LREC 2022 • Erik Cambria, Qian Liu, Sergio Decherchi, Frank Xing, Kenneth Kwok
In recent years, AI research has demonstrated enormous potential for the benefit of humanity and society.
1 code implementation • 6 Nov 2024 • Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang, Fabian Isensee, Zifu Wang, Jieneng Chen, Yu-Cheng Chou, Yannick Kirchhoff, Maximilian Rokuss, Ziyan Huang, Jin Ye, Junjun He, Tassilo Wald, Constantin Ulrich, Michael Baumgartner, Saikat Roy, Klaus H. Maier-Hein, Paul Jaeger, Yiwen Ye, Yutong Xie, Jianpeng Zhang, Ziyang Chen, Yong Xia, Zhaohu Xing, Lei Zhu, Yousef Sadegheih, Afshin Bozorgpour, Pratibha Kumari, Reza Azad, Dorit Merhof, Pengcheng Shi, Ting Ma, Yuxin Du, Fan Bai, Tiejun Huang, Bo Zhao, Haonan Wang, Xiaomeng Li, Hanxue Gu, Haoyu Dong, Jichen Yang, Maciej A. Mazurowski, Saumya Gupta, Linshan Wu, Jiaxin Zhuang, Hao Chen, Holger Roth, Daguang Xu, Matthew B. Blaschko, Sergio Decherchi, Andrea Cavalli, Alan L. Yuille, Zongwei Zhou
We are committed to expanding this benchmark to encourage more innovation of AI algorithms for the medical domain.
1 code implementation • 5 Nov 2024 • Pedro R. A. S. Bassi, Qilong Wu, Wenxuan Li, Sergio Decherchi, Andrea Cavalli, Alan Yuille, Zongwei Zhou
Label Critic can also check the label quality of a single AI Label with 71. 8% accuracy when no alternatives are available for comparison, prompting radiologists to review and edit if the estimated quality is low (19% depending on body structures).
no code implementations • 24 Jul 2024 • Celeste Damiani, Yulia Rodina, Sergio Decherchi
Federated learning is becoming an increasingly viable and accepted strategy for building machine learning models in critical privacy-preserving scenarios such as clinical settings.
no code implementations • 13 Jul 2024 • Pedro R. A. S. Bassi, Andrea Cavalli, Sergio Decherchi
We found that it is possible to train a neural network with explanation (e. g by Layer Relevance Propagation, LRP) distillation only, and that the technique leads to high resistance to shortcut learning, surpassing group-invariant learning, explanation background minimization, and alternative distillation techniques.
1 code implementation • 16 Jan 2024 • Pedro R. A. S. Bassi, Sergio Decherchi, Andrea Cavalli
Representing a potentially massive training speed improvement over ISNet, the proposed architectures introduce LRP optimization into a gamut of applications that the original model cannot feasibly handle.
no code implementations • 29 Sep 2021 • Erika Gardini, Andrea Cavalli, Sergio Decherchi
One-class learning through deep architectures is a particularly challenging task; in this scenario the crasis of kernel methods and deep networks can represent a viable strategy to empower already effective methods.
no code implementations • 9 Oct 2017 • Marco Jacopo Ferrarotti, Sergio Decherchi, Walter Rocchia
However, the systematic application of the kernelized version of k-means is hampered by its inherent square scaling in memory with the number of samples.