no code implementations • CCL 2021 • Chao Sun, Weiguang Qu, Tingxin Wei, Yanhui Gu, Bin Li, Junsheng Zhou
“连动句是形如“NP+VP1+VP2”的句子, 句中含有两个或两个以上的动词(或动词结构)且动词的施事为同一对象。相同结构的连动句可以表示多种不同的语义关系。本文基于前人对连动句中VP1和VP2之间的语义关系分类, 标注了连动句语义关系数据集, 基于神经网络完成了对连动句语义关系的识别。该方法将连动句语义识别任务进行分解, 基于BERT进行编码, 利用BiLSTM-CRF先识别出连动句中连动词(VP)及其主语(NP), 再基于融合连动词信息的编码, 利用BiLSTM-Attention对连动词进行关系判别, 实验结果验证了所提方法的有效性。”
no code implementations • CCL 2020 • Chao Sun, Weiguang Qu, Tingxin Wei, Yanhui Gu, Bin Li, Junsheng Zhou
连动句是具有连动结构的句子, 是汉语中的特殊句法结构, 在现代汉语中十分常见且使用频繁。连动句语法结构和语义关系都很复杂, 在识别中存在许多问题, 对此本文针对连动句的识别问题进行了研究, 提出了一种基于神经网络的连动句识别方法。本方法分两步:第一步, 运用简单的规则对语料进行预处理;第二步, 用文本分类的思想, 使用BERT编码, 利用多层CNN与BiLSTM模型联合提取特征进行分类, 进而完成连动句识别任务。在人工标注的语料上进行实验, 实验结果达到92. 71%的准确率, F1值为87. 41%。
no code implementations • 20 Mar 2024 • Wei Wang, Naike Du, Yuchao Guo, Chao Sun, Jingyang Liu, Rencheng Song, Xiuzhu Ye
The radar signal processing algorithm is one of the core components in through-wall radar human detection technology.
no code implementations • 6 Mar 2024 • Ting Zhang, Hao Zhou, Hainan Wu, Hanwen Sunchu, Lei Hu, Xiaofang Chen, Suyuan Zhao, Gaochao liu, Chao Sun, Jiahuan Zhang, Yizhen Luo, Peng Liu, Zaiqing Nie, Yushuai Wu
The fields of therapeutic application and drug research and development (R&D) both face substantial challenges, i. e., the therapeutic domain calls for more treatment alternatives, while numerous promising pre-clinical drugs have failed in clinical trials.
no code implementations • 7 Jan 2024 • Chao Zhang, Yongxiang Guo, Dawid Sheng, Zhixiong Ma, Chao Sun, Yuwei Zhang, Wenxin Zhao, Fenyan Zhang, Tongfei Wang, Xing Sheng, Milin Zhang
This work presents the first fabricated electrophysiology-optogenetic closed-loop bidirectional brain-machine interface (CL-BBMI) system-on-chip (SoC) with electrical neural signal recording, on-chip sleep staging and optogenetic stimulation.
no code implementations • 22 Feb 2023 • Minghai Qin, Chao Sun, Jaco Hofmann, Dejan Vucinic
For example, each layer of a ResNet-50 model can be distributively inferred across two nodes with five times less data communications, almost half overall computations and half memory requirement for a single node, and achieve comparable accuracy to the original ResNet-50 model.
1 code implementation • 21 Jul 2022 • Jennifer J. Sun, Markus Marks, Andrew Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Sebastian Oleszko, Zachary Partridge, Milan Peelman, Alice Robie, Catherine E. Schretter, Keith Sheppard, Chao Sun, Param Uttarwar, Julian M. Wagner, Eric Werner, Joseph Parker, Pietro Perona, Yisong Yue, Kristin Branson, Ann Kennedy
We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations.
no code implementations • 3 Dec 2021 • Junming Cao, Bihuan Chen, Chao Sun, Longjie Hu, Shuaihong Wu, Xin Peng
To bridge this gap, we present the first comprehensive study to i) characterize symptoms, root causes, and introducing and exposing stages of PPs in DL systems developed in TensorFLow and Keras, with 224 PPs collected from 210 StackOverflow posts, and to ii) assess the capability of existing performance analysis approaches in tackling PPs, with a constructed benchmark of 58 PPs in DL systems.
no code implementations • 13 Oct 2021 • Zhiming Liu, Xuefei Zhang, Chongyang Liu, Hao Wang, Chao Sun, Bin Li, Weifeng Sun, Pu Huang, Qingjun Li, Yu Liu, Haipeng Kuang, Jihong Xiu
To address these issues, we propose a relationship representation network for object detection in aerial images (RelationRS): 1) Firstly, multi-scale features are fused and enhanced by a dual relationship module (DRM) with conditional convolution.
1 code implementation • 1 Sep 2021 • Chao Sun, Zhedong Zheng, Xiaohan Wang, Mingliang Xu, Yi Yang
Albeit simple, the pre-trained encoder can capture the key points of an unseen point cloud and surpasses the encoder trained from scratch on downstream tasks.
Ranked #43 on 3D Part Segmentation on ShapeNet-Part
no code implementations • 10 Aug 2021 • Zan Gao, Chao Sun, Zhiyong Cheng, Weili Guan, AnAn Liu, Meng Wang
In this work, a novel end-to-end two-stream boundary-aware network (abbreviated as TBNet) is proposed for generic image manipulation localization in which the RGB stream, the frequency stream, and the boundary artifact location are explored in a unified framework.
no code implementations • 28 Jun 2021 • Chao Sun, Victor Guang Shi
To take advantage of both models, this paper proposed a model that combines the physics-based model and the neural network model to improve the prediction accuracy for the whole life cycle of a system.
no code implementations • 18 Jun 2021 • Chao Sun, Javier Dominguez-Caballero, Rob Ward, Sabino Ayvar-Soberanis, David Curtis
This method showed that neural network models have the capability to learn the behavior of a complex machine tool system and predict cycle times.
1 code implementation • 22 Dec 2020 • Ziqi Wang, Linfeng Jiang, Yihong Du, Chao Sun, Enrico Calzavarini
We propose a boundary-layer model and a buoyancy-intensity model which account for the main features of the ice morphology.
Fluid Dynamics Geophysics
1 code implementation • 10 Dec 2020 • Linfeng Jiang, Cheng Wang, Shuang Liu, Chao Sun, Enrico Calzavarini
We successfully perform the three-dimensional tracking in a turbulent fluid flow of small asymmetrical particles that are neutrally-buoyant and bottom-heavy, i. e., they have a non-homogeneous mass distribution along their symmetry axis.
Fluid Dynamics
1 code implementation • 30 Nov 2019 • Linfeng Jiang, Enrico Calzavarini, Chao Sun
Inertialess anisotropic particles in a Rayleigh-B\'enard turbulent flow show maximal tumbling rates for weakly oblate shapes, in contrast with the universal behaviour observed in developed turbulence where the mean tumbling rate monotonically decreases with the particle aspect ratio.
Fluid Dynamics Soft Condensed Matter
no code implementations • WS 2017 • Ye Tian, Thiago Galery, Giulio Dulcinati, Emilia Molimpakis, Chao Sun
FB reactions (e. g. {``}Love{''} and {``}Angry{''}) indicate the readers{'} overall sentiment, against which we can investigate the types of emojis used the comments under different reaction profiles.