1 code implementation • 19 Oct 2020 • Long Chen, Feixiang Zhou, Shengke Wang, Junyu Dong, Ning li, Haiping Ma, Xin Wang, Huiyu Zhou
Moreover, inspired by the human education process that drives the learning from easy to hard concepts, we here propose the CMA training paradigm that first trains a clean detector which is free from the influence of noisy data.
1 code implementation • 23 May 2020 • Long Chen, Zhihua Liu, Lei Tong, Zheheng Jiang, Shengke Wang, Junyu Dong, Huiyu Zhou
In addition, we propose a novel sample-weighted loss function which can model sample weights for SWIPENet, which uses a novel sample re-weighting algorithm, namely Invert Multi-Class Adaboost (IMA), to reduce the influence of noise on the proposed SWIPENet.
no code implementations • Journal of Visual Communication and Image Representation 2019 • Yongqiang Kong, Jianhui Huang, Shanshan Huang, Zhengang Wei, Shengke Wang
Finally, we apply voting on the results of event classification to perform multicamera fall detection.
no code implementations • 28 Feb 2017 • Long Chen, Junyu Dong, Shengke Wang, Kin-Man Lam, Muwei Jian, Hua Zhang, Xiaochun Cao
To bridge this gap, we introduce a cascaded structure to eliminate background and exploit a one-vs-rest loss to capture more minute variances among different subordinate categories.