no code implementations • 28 Feb 2022 • Mengshuo Jia, Gabriela Hug, Yifan Su, Chen Shen
Given the increased percentage of wind power in power systems, chance-constrained optimal power flow (CC-OPF) calculation, as a means to take wind power uncertainty into account with a guaranteed security level, is being promoted.
no code implementations • 28 Feb 2022 • Mengshuo Jia, Qianni Cao, Chen Shen, Gabriela Hug
This method is based on a high-precision linear power flow model, whose precision is even further improved in this paper by an original correction approach.
no code implementations • 9 Feb 2022 • Chen Shen, Yi Liu, Wenzhi Fan, Bin Wang, Shixue Wen, Yao Tian, Jun Zhang, Jingsheng Yang, Zejun Ma
For Track 1, we propose several approaches to empower the clustering-based speaker diarization system to handle overlapped speech.
no code implementations • 8 Oct 2021 • Shaoshi Ling, Chen Shen, Meng Cai, Zejun Ma
In the recent trend of semi-supervised speech recognition, both self-supervised representation learning and pseudo-labeling have shown promising results.
no code implementations • 19 Aug 2021 • Chen Shen, Pochuan Wang, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Weichung Wang, Chiou-Shann Fuh, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Kensaku MORI
Federated learning (FL) for medical image segmentation becomes more challenging in multi-task settings where clients might have different categories of labels represented in their data.
1 code implementation • 25 May 2021 • Xiao Luo, Daqing Wu, Chong Chen, Jinwen Ma, Minghua Deng, Chen Shen, Jianqiang Huang, Xian-Sheng Hua
Besides, CHCF integrates criterion learning and user preference learning into a unified framework, which can be trained jointly for the interaction prediction on target behavior.
no code implementations • 19 May 2021 • Qianni Cao, Chen Shen, Mengshuo Jia
Then, an orientation independent vector C is developed to eliminate the probability distribution differences of power outputs caused by varying azimuth angles and tilt angles.
no code implementations • 1 Jan 2021 • Yue Wu, Jianqiang Huang, Jiangjie Zhen, Guokun Wang, Chen Shen, Chang Zhou, Xian-Sheng Hua
The past years have witnessed an explosion of deep learning frameworks like PyTorch and TensorFlow since the success of deep neural networks.
no code implementations • 28 Oct 2020 • Zhonghao Li, Benlai Tang, Xiang Yin, Yuan Wan, Ling Xu, Chen Shen, Zejun Ma
Singing voice conversion (SVC) aims to convert the voice of one singer to that of other singers while keeping the singing content and melody.
no code implementations • 28 Sep 2020 • Pochuan Wang, Chen Shen, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Kazunari Misawa, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Wei-Chung Wang, Kensaku MORI
The performance of deep learning-based methods strongly relies on the number of datasets used for training.
1 code implementation • 2 Sep 2020 • Shaotian Yan, Chen Shen, Zhongming Jin, Jianqiang Huang, Rongxin Jiang, Yaowu Chen, Xian-Sheng Hua
Today, scene graph generation(SGG) task is largely limited in realistic scenarios, mainly due to the extremely long-tailed bias of predicate annotation distribution.
Ranked #3 on
Unbiased Scene Graph Generation
on Visual Genome
no code implementations • 14 Aug 2020 • Lihong He, Chen Shen, Arjun Mukherjee, Slobodan Vucetic, Eduard Dragut
We show that the early arrival rate of comments is the best indicator of the eventual number of comments.
no code implementations • 7 Aug 2019 • Chen Shen, Rongrong Ji, Fuhai Chen, Xiaoshuai Sun, Xiangming Li
Specifically, the proposed module first embeds the scene concepts into factored weights explicitly and attends the visual information extracted from the input image.
no code implementations • 17 Dec 2018 • Mengshuo Jia, Shaowei Huang, Zhiwen Wang, Chen Shen
Establishing the joint probability distribution of wind power and the corresponding forecast data of spatially correlated WFs is the foundation for deriving the conditional probability distribution.
no code implementations • 6 Jun 2018 • Holger R. Roth, Chen Shen, Hirohisa ODA, Takaaki Sugino, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku MORI
Recent advances in deep learning, like 3D fully convolutional networks (FCNs), have improved the state-of-the-art in dense semantic segmentation of medical images.
no code implementations • 7 May 2018 • Chen Shen, Guo-Jun Qi, Rongxin Jiang, Zhongming Jin, Hongwei Yong, Yaowu Chen, Xian-Sheng Hua
In this paper, we present novel sharp attention networks by adaptively sampling feature maps from convolutional neural networks (CNNs) for person re-identification (re-ID) problem.
no code implementations • 23 Mar 2018 • Holger R. Roth, Chen Shen, Hirohisa ODA, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku MORI
However, recent advances in deep learning have made it possible to significantly improve the performance of image recognition and semantic segmentation methods in the field of computer vision.
no code implementations • 18 Jan 2018 • Chen Shen, Holger R. Roth, Hirohisa ODA, Masahiro Oda, Yuichiro Hayashi, Kazunari Misawa, Kensaku MORI
Deep learning-based methods achieved impressive results for the segmentation of medical images.
no code implementations • 23 Oct 2017 • Feipeng Zhao, Martin Renqiang Min, Chen Shen, Amit Chakraborty
In this paper, we try to learn more complex connections between entities and relationships.