no code implementations • CCL 2020 • Huijun Hu, Cong Wang, Jianhua Dai, Maofu Liu
社会突发事件的分类和等级研判作为应急处置中的一环, 其重要性不言而喻。然而, 目前研究多数采用人工或规则的方法识别证据进行研判, 由于社会突发事件的构成的复杂性和语言描述的灵活性, 这对于研判证据识别有很大局限性。本文参考“事件抽取”思想, 事件类型和研判证据作为事件中元素, 以BiLSTM-CRF方法细粒度的识别, 并将二者结合, 分类结果作为等级研判的输入, 识别出研判证据。最终将识别结果结合注意力机制进行等级研判, 通过对研判证据的精准识别从而来增强等级研判的准确性。实验表明, 相比人工或规则识别研判证据, 本文提出的方法有着更好的鲁棒性, 社会突发事件研判时也达到了较好的效果。 关键词:事件分类 ;研判证据识别 ;等级研判 ;BiLSTM-CRF
no code implementations • 4 Jun 2024 • Cong Wang, Kuan Tian, Jun Zhang, Yonghang Guan, Feng Luo, Fei Shen, Zhiwei Jiang, Qing Gu, Xiao Han, Wei Yang
In our work on portrait video generation, we identified audio signals as particularly weak, often overshadowed by stronger signals such as facial pose and reference image.
1 code implementation • 2 Jun 2024 • Cong Wang, Jinshan Pan, Wei Wang, Gang Fu, Siyuan Liang, Mengzhu Wang, Xiao-Ming Wu, Jun Liu
To better improve feature representation in low-resolution space, we propose to build feature transformation from the high-resolution space to the low-resolution one.
1 code implementation • 2 Jun 2024 • Cong Wang, Wei Wang, Chengjin Yu, Jie Mu
To better model this property for image detaining, we develop a multi-scale graph network with exemplars, called MSGNN, that contains two branches: 1) internal data-based supervised branch is used to model the internal relations of similar patches from the rainy image itself and its multi-scale images and 2) external data-participated unsupervised branch is used to model the external relations of the similar patches in the rainy image and exemplar.
1 code implementation • 27 May 2024 • Cong Wang, Kuan Tian, Yonghang Guan, Jun Zhang, Zhiwei Jiang, Fei Shen, Xiao Han, Qing Gu, Wei Yang
In this paper, we propose a novel ensembling method, Adaptive Feature Aggregation (AFA), which dynamically adjusts the contributions of multiple models at the feature level according to various states (i. e., prompts, initial noises, denoising steps, and spatial locations), thereby keeping the advantages of multiple diffusion models, while suppressing their disadvantages.
no code implementations • 29 Apr 2024 • Cong Wang, Di Kang, He-Yi Sun, Shen-Han Qian, Zi-Xuan Wang, Linchao Bao, Song-Hai Zhang
In this paper, we propose a Hybrid Mesh-Gaussian Head Avatar (MeGA) that models different head components with more suitable representations.
no code implementations • 28 Apr 2024 • Zilong Bai, ruiji zhang, Linqing Chen, Qijun Cai, Yuan Zhong, Cong Wang, Yan Fang, Jie Fang, Jing Sun, Weikuan Wang, Lizhi Zhou, Haoran Hua, Tian Qiu, Chaochao Wang, Cheng Sun, Jianping Lu, Yixin Wang, Yubin Xia, Meng Hu, Haowen Liu, Peng Xu, Licong Xu, Fu Bian, Xiaolong Gu, Lisha Zhang, Weilei Wang, Changyang Tu
In recent years, large language models(LLMs) have attracted significant attention due to their exceptional performance across a multitude of natural language process tasks, and have been widely applied in various fields.
1 code implementation • 17 Apr 2024 • Jie Xu, Zihan Wu, Cong Wang, Xiaohua Jia
To address the growing demand for privacy protection in machine learning, we propose a novel and efficient machine unlearning approach for \textbf{L}arge \textbf{M}odels, called \textbf{LM}Eraser.
no code implementations • 15 Mar 2024 • Cong Wang, Jinshan Pan, Yeying Jin, Liyan Wang, Wei Wang, Gang Fu, Wenqi Ren, Xiaochun Cao
Our designs provide a closer look at the attention mechanism and reveal that some simple operations can significantly affect the model performance.
no code implementations • 2 Feb 2024 • Hao Li, Wei Wang, Cong Wang, Zhigang Luo, Xinwang Liu, Kenli Li, Xiaochun Cao
Single-domain generalized object detection aims to enhance a model's generalizability to multiple unseen target domains using only data from a single source domain during training.
no code implementations • 26 Jan 2024 • Haoning Li, Cong Wang, Qinghua Huang
To do so, this paper employs iterative feature selection in fuzzy rule-based binary classification.
1 code implementation • 27 Dec 2023 • Qifei Li, Yingming Gao, Cong Wang, Yayue Deng, Jinlong Xue, Yichen Han, Ya Li
To address this problem, we propose a frame-level emotional state alignment method for SER.
no code implementations • 6 Dec 2023 • Siguo Bi, Kai Li, Shuyan Hu, Wei Ni, Cong Wang, Xin Wang
Detecting spoofing attacks on the positions of unmanned aerial vehicles (UAVs) within a swarm is challenging.
no code implementations • 5 Dec 2023 • Cong Wang, Jiaxi Gu, Panwen Hu, Songcen Xu, Hang Xu, Xiaodan Liang
Especially for fidelity, our model has a powerful image retention ability and delivers the best results in UCF101 compared to other image-to-video models to our best knowledge.
1 code implementation • 28 Nov 2023 • Zhantao Chen, Cong Wang, Mingye Gao, Chun Hong Yoon, Jana B. Thayer, Joshua J. Turner
The development of X-ray Free Electron Lasers (XFELs) has opened numerous opportunities to probe atomic structure and ultrafast dynamics of various materials.
1 code implementation • 25 Oct 2023 • Cong Wang, Xiaofeng Cao, Lanzhe Guo2, Zenglin Shi
In this paper, we propose a novel SSL method called DualMatch, in which the class prediction jointly invokes feature embedding in a dual-level interaction manner.
no code implementations • 11 Oct 2023 • Jiamin Li, Qiang Su, Yitao Yang, Yimin Jiang, Cong Wang, Hong Xu
Existing MoE model adopts a fixed gating network where each token is computed by the same number of experts.
1 code implementation • 10 Oct 2023 • Fei Shen, Hu Ye, Jun Zhang, Cong Wang, Xiao Han, Wei Yang
Specifically, in the first stage, we design a simple prior conditional diffusion model that predicts the global features of the target image by mining the global alignment relationship between pose coordinates and image appearance.
no code implementations • 2 Oct 2023 • Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Ewa Deelman, Prasanna Balaprakash
To address this problem, we introduce an autoencoder-driven self-supervised learning~(SSL) approach that learns a summary statistic from unlabeled workflow data and estimates the normal behavior of the computational workflow in the latent space.
1 code implementation • 17 Aug 2023 • Liyan Wang, Qinyu Yang, Cong Wang, Wei Wang, Jinshan Pan, Zhixun Su
Specifically, our C2F-DFT contains diffusion self-attention (DFSA) and diffusion feed-forward network (DFN) within a new coarse-to-fine training scheme.
1 code implementation • 14 Aug 2023 • Jie Xu, Zihan Wu, Cong Wang, Xiaohua Jia
Machine learning models may inadvertently memorize sensitive, unauthorized, or malicious data, posing risks of privacy breaches, security vulnerabilities, and performance degradation.
no code implementations • ICCV 2023 • Cong Wang, Yu-Ping Wang, Dinesh Manocha
We demonstrate the effectiveness of our approach and generate state-of-the-art results on different datasets.
no code implementations • 11 Jul 2023 • Cong Wang, Di Kang, Yan-Pei Cao, Linchao Bao, Ying Shan, Song-Hai Zhang
Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications.
1 code implementation • 6 Jun 2023 • Sen Peng, Yufei Chen, Cong Wang, Xiaohua Jia
This paper introduces WDM, a novel watermarking solution for diffusion models without imprinting the watermark during task generation.
1 code implementation • 4 May 2023 • Xiang Zheng, Xingjun Ma, Shengjie Wang, Xinyu Wang, Chao Shen, Cong Wang
Our experiments validate the effectiveness of the four types of adversarial intrinsic regularizers and the bias-reduction method in enhancing black-box adversarial policy learning across a variety of environments.
no code implementations • 9 Apr 2023 • Yanru Xiao, Cong Wang, Xing Gao
The vulnerability in the algorithm supply chain of deep learning has imposed new challenges to image retrieval systems in the downstream.
no code implementations • 24 Mar 2023 • Cong Wang, Po-Nan Li, Jana Thayer, Chun Hong Yoon
PeakNet is well-suited for expert-level real-time serial crystallography data analysis at high data rates.
1 code implementation • 13 Mar 2023 • Cong Wang, Jinshan Pan, WanYu Lin, Jiangxin Dong, Xiao-Ming Wu
For this purpose, we develop a prompt based on the features of depth differences between the hazy input images and corresponding clear counterparts that can guide dehazing models for better restoration.
no code implementations • 11 Mar 2023 • Yu-Jia An, Sheng-Chen Bai, Lin Cheng, Xiao-Guang Li, Cheng-en Wang, Xiao-Dong Han, Gang Su, Shi-Ju Ran, Cong Wang
The accuracy of the samples with high certainty is almost 100$\%$.
1 code implementation • 1 Mar 2023 • Cong Wang, Zhiwei Jiang, Yafeng Yin, Zifeng Cheng, Shiping Ge, Qing Gu
For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes.
no code implementations • 14 Feb 2023 • Cong Wang, Eric Florin, Hsing-Yin Chang, Jana Thayer, Chun Hong Yoon
With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature.
no code implementations • 19 Jan 2023 • Peter I Renn, Cong Wang, Sahin Lale, Zongyi Li, Anima Anandkumar, Morteza Gharib
The learned FNO solution operator can be evaluated in milliseconds, potentially enabling faster-than-real-time modeling for predictive flow control in physical systems.
no code implementations • 28 Nov 2022 • Xiang Zheng, Xingjun Ma, Cong Wang
Intrinsic motivation is a promising exploration technique for solving reinforcement learning tasks with sparse or absent extrinsic rewards.
no code implementations • 15 Nov 2022 • Heyu Huang, Runmin Cong, Lianhe Yang, Ling Du, Cong Wang, Sam Kwong
The feedback chain structure unit learns deeper and wider feature representation of each encoder layer through the hierarchical feature aggregation feedback chains, and achieves feature selection and feedback through the feature handover attention module.
1 code implementation • 1 Nov 2022 • Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang
In this paper, we investigate the third type of exploitation of data poisoning - increasing the risks of privacy leakage of benign training samples.
2 code implementations • Proceedings of the 30th ACM International Conference on Multimedia 2022 • He Li, Mang Ye, Cong Wang, Bo Do
The robust and discriminative feature extraction is the key component in person re-identification (Re-ID).
no code implementations • 27 Jul 2022 • Cong Wang, Hongmin Xu, Xiong Zhang, Li Wang, Zhitong Zheng, Haifeng Liu
Vision Transformers (ViTs) have recently dominated a range of computer vision tasks, yet it suffers from low training data efficiency and inferior local semantic representation capability without appropriate inductive bias.
3 code implementations • 17 Jul 2022 • Runmin Cong, Haowei Yang, Qiuping Jiang, Wei Gao, Haisheng Li, Cong Wang, Yao Zhao, Sam Kwong
The spread of COVID-19 has brought a huge disaster to the world, and the automatic segmentation of infection regions can help doctors to make diagnosis quickly and reduce workload.
no code implementations • 16 Jul 2022 • Cong Wang, Jinshan Pan, Xiao-Ming Wu
The generator is based on a U-shaped Transformer which is used to explore non-local information for better clear image restoration.
3 code implementations • 20 Jun 2022 • Xudong Tian, Zhizhong Zhang, Cong Wang, Wensheng Zhang, Yanyun Qu, Lizhuang Ma, Zongze Wu, Yuan Xie, DaCheng Tao
Information Bottleneck (IB) based multi-view learning provides an information theoretic principle for seeking shared information contained in heterogeneous data descriptions.
no code implementations • 7 May 2022 • Prajval Kumar Murali, Cong Wang, Ravinder Dahiya, Mohsen Kaboli
Three-dimensional (3D) object recognition is crucial for intelligent autonomous agents such as autonomous vehicles and robots alike to operate effectively in unstructured environments.
no code implementations • 29 Apr 2022 • Cong Wang, Bin Hu, Hongyi Wu
Energy is an essential, but often forgotten aspect in large-scale federated systems.
1 code implementation • 16 Apr 2022 • Zifeng Cheng, Zhiwei Jiang, Yafeng Yin, Cong Wang, Qing Gu
In our method, soft labeling is used to reshape the label distribution of the known intent samples, aiming at reducing model's overconfident on known intents.
no code implementations • 29 Mar 2022 • Jingting Zhang, Chengzhi Yuan, Wei Zeng, Cong Wang
This paper proposes a novel fault detection and isolation (FDI) scheme for distributed parameter systems modeled by a class of parabolic partial differential equations (PDEs) with nonlinear uncertain dynamics.
no code implementations • 14 Mar 2022 • Yi Liu, Lei Xu, Xingliang Yuan, Cong Wang, Bo Li
Existing machine unlearning techniques focus on centralized training, where access to all holders' training data is a must for the server to conduct the unlearning process.
no code implementations • 7 Mar 2022 • Zhe Chen, Cong Wang
We present sufficient conditions for the load-flow solvability under security constraints in DC distribution networks.
no code implementations • 2 Mar 2022 • Qingfeng Yao, Jilong Wan, Shuyu Yang, Cong Wang, Linghan Meng, Qifeng Zhang, Donglin Wang
Due to their ability to adapt to different terrains, quadruped robots have drawn much attention in the research field of robot learning.
no code implementations • 2 Mar 2022 • Qingfeng Yao, Jilong Wang, Shuyu Yang, Cong Wang, Hongyin Zhang, Qifeng Zhang, Donglin Wang
The deep learning model extracts key points during animal motion from videos.
no code implementations • 16 Feb 2022 • Jiamin Li, Hong Xu, Yibo Zhu, Zherui Liu, Chuanxiong Guo, Cong Wang
We introduce Aryl, a new cluster scheduler to address these problems.
no code implementations • 14 Feb 2022 • Cong Wang, Jinshan Pan, Xiao-Ming Wu
Most of the existing deep-learning-based methods constrain the network to generate derained images but few of them explore features from intermediate layers, different levels, and different modules which are beneficial for rain streaks removal.
no code implementations • 4 Feb 2022 • Yifeng Zheng, Shangqi Lai, Yi Liu, Xingliang Yuan, Xun Yi, Cong Wang
In this paper, we present a system design which offers efficient protection of individual model updates throughout the learning procedure, allowing clients to only provide obscured model updates while a cloud server can still perform the aggregation.
no code implementations • 23 Jan 2022 • WanYu Lin, Baochun Li, Cong Wang
It is typical to collect these local views of social graphs and conduct graph learning tasks.
no code implementations • 6 Dec 2021 • Cong Wang, Tongwei Lu
This paper provides a complexity analysis for the game of dark Chinese chess (a. k. a.
1 code implementation • 6 Dec 2021 • Jianye Hao, Yifu Yuan, Cong Wang, Zhen Wang
Model-based reinforcement learning (MBRL) achieves significant sample efficiency in practice in comparison to model-free RL, but its performance is often limited by the existence of model prediction error.
1 code implementation • 4 Dec 2021 • Yiheng Sun, Tian Lu, Cong Wang, Yuan Li, Huaiyu Fu, Jingran Dong, Yunjie Xu
The prosperity of mobile and financial technologies has bred and expanded various kinds of financial products to a broader scope of people, which contributes to advocating financial inclusion.
1 code implementation • MM - Proceedings of the ACM International Conference on Multimedia 2021 • Yunjie Ge, Qian Wang, Baolin Zheng, Xinlu Zhuang, Qi Li, Chao Shen, Cong Wang
In this paper, we, for the first time, propose a novel Anti-Distillation Backdoor Attack (ADBA), in which the backdoor embedded in the public teacher model can survive the knowledge distillation process and thus be transferred to secret distilled student models.
no code implementations • 19 Oct 2021 • Baolin Zheng, Peipei Jiang, Qian Wang, Qi Li, Chao Shen, Cong Wang, Yunjie Ge, Qingyang Teng, Shenyi Zhang
For commercial cloud speech APIs, we propose Occam, a decision-only black-box adversarial attack, where only final decisions are available to the adversary.
no code implementations • 29 Sep 2021 • Cong Wang, Jun He, Yu Chen, Xiufen Zou
Although differential evolution (DE) algorithms perform well on a large variety of complicated optimization problems, only a few theoretical studies are focused on the working principle of DE algorithms.
1 code implementation • 14 Sep 2021 • Cong Wang, Yu-Ping Wang, Dinesh Manocha
A key aspect of our approach is to use an appropriate motion model that can help existing self-supervised monocular VO (SSM-VO) algorithms to overcome issues related to the local minima within their self-supervised loss functions.
no code implementations • 25 Aug 2021 • Cong Wang, Yan Huang, Yuexian Zou, Yong Xu
However, it is noted that ASM-based SIDM degrades its performance in dehazing real world hazy images due to the limited modelling ability of ASM where the atmospheric light factor (ALF) and the angular scattering coefficient (ASC) are assumed as constants for one image.
1 code implementation • Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) 2021 • Mingjie Li, Wenjia Cai, Rui Liu, Yuetian Weng, Xiaoyun Zhao, Cong Wang, Xin Chen, Zhong Liu, Caineng Pan, Mengke Li, Yizhi Liu, Flora D Salim, Karin Verspoor, Xiaodan Liang, Xiaojun Chang
Researchers have explored advanced methods from computer vision and natural language processing to incorporate medical domain knowledge for the generation of readable medical reports.
no code implementations • 8 Aug 2021 • Cong Wang, Haocheng Han, Caleb Chen Cao
Explanation of AI, as well as fairness of algorithms' decisions and the transparency of the decision model, are becoming more and more important.
2 code implementations • 23 Jun 2021 • Yufei Chen, Chao Shen, Cong Wang, Yang Zhang
To this end, we propose a teacher model fingerprinting attack to infer the origin of a student model, i. e., the teacher model it transfers from.
no code implementations • CVPR 2021 • Yanru Xiao, Cong Wang
In this paper, we start from an adversarial standpoint to explore and enhance the capacity of targeted black-box transferability attack for deep hashing.
1 code implementation • 12 Jun 2021 • Dian Chen, Hongxin Hu, Qian Wang, Yinli Li, Cong Wang, Chao Shen, Qi Li
In deep learning, a typical strategy for transfer learning is to freeze the early layers of a pre-trained model and fine-tune the rest of its layers on the target domain.
no code implementations • 21 Jan 2021 • Cong Wang, Yan Huang, Yuexian Zou, Yong Xu
However, for images taken in real-world, the illumination is not uniformly distributed over whole image which brings model mismatch and possibly results in color shift of the deep models using ASM.
no code implementations • 8 Dec 2020 • Yi Liu, Xingliang Yuan, Ruihui Zhao, Cong Wang, Dusit Niyato, Yefeng Zheng
Extensive case studies have shown that our attacks are effective on different datasets and common semi-supervised learning methods.
1 code implementation • 9 Oct 2020 • Yuanjun Yao, Qiang Cao, Paul Ruth, Mert Cevik, Cong Wang, Jeff Chase
Research testbed fabrics have potential to support long-lived, evolving, interdomain experiments, including opt-in application traffic across multiple campuses and edge sites.
Networking and Internet Architecture
1 code implementation • 6 Aug 2020 • Cong Wang, Yutong Wu, Zhixun Su, Junyang Chen
In the field of multimedia, single image deraining is a basic pre-processing work, which can greatly improve the visual effect of subsequent high-level tasks in rainy conditions.
no code implementations • 3 Aug 2020 • Cong Wang, Xiaoying Xing, Zhixun Su, Junyang Chen
Further, we design an inner-scale connection block to utilize the multi-scale information and features fusion way between different scales to improve rain representation ability and we introduce the dense block with skip connection to inner-connect these blocks.
no code implementations • 20 Jun 2020 • Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou, Shuzhi Sam Ge
G-images refer to image data defined on irregular graph domains.
no code implementations • 10 Jun 2020 • Cong Wan, Shan Jiang, Cuirong Wang, Cong Wang, Changming Xu, Xianxia Chen, Ying Yuan
We use an unsupervised neural sentence embedding model to map the blogs to an embedding space.
no code implementations • 7 Jun 2020 • Cong Wang, Qifeng Zhang, Qiyan Tian, Shuo Li, Xiaohui Wang, David Lane, Yvan Petillot, Ziyang Hong, Sen Wang
Tracking and grasping a dynamic object with a random trajectory is even harder.
no code implementations • 26 May 2020 • Cong Wang, Yanru Xiao, Xing Gao, Li Li, Jun Wang
We show the feasibility of training with mobile CPUs, where training 100 epochs takes less than 10 mins and can be boosted 3-5 times with feature transfer.
no code implementations • 25 May 2020 • Cong Wang, Yuanyuan Yang, Pengzhan Zhou
While the current research mainly focuses on optimizing learning algorithms and minimizing communication overhead left by distributed learning, there is still a considerable gap when it comes to the real implementation on mobile devices.
no code implementations • 15 Apr 2020 • Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou
Due to its inferior characteristics, an observed (noisy) image's direct use gives rise to poor segmentation results.
no code implementations • 30 Mar 2020 • Honghe Zhu, Cong Wang, Ya-Jie Zhang, Zhixun Su, Guohui Zhao
Single image deraining is an urgent task because the degraded rainy image makes many computer vision systems fail to work, such as video surveillance and autonomous driving.
1 code implementation • 11 Mar 2020 • Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu
Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection.
no code implementations • 21 Feb 2020 • Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou
Considering these feature sets as data of clustering, an modified FCM algorithm is proposed, which introduces a KL divergence term in the partition matrix into its objective function.
no code implementations • 14 Feb 2020 • Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou, Jun Zhao
To further enhance the segmentation effects of the improved FCM algorithm, we also employ the morphological reconstruction to smoothen the labels generated by clustering.
no code implementations • 12 Nov 2019 • Qiao Zhang, Cong Wang, Chunsheng Xin, Hongyi Wu
This significant speedup enables a wide range of practical applications based on privacy-preserved deep neural networks.
no code implementations • 3 Sep 2019 • Cong Wang, Yu Chen, Jun He, Chengwang Xie
When globally optimal solutions of complicated optimization problems cannot be located by evolutionary algorithms (EAs) in polynomial expected running time, the hitting time/running time analysis is not flexible enough to accommodate the requirement of theoretical study, because sometimes we have no idea on what approximation ratio is available in polynomial expected running time.
no code implementations • 29 Aug 2019 • Bang Wu, Shuo Wang, Xingliang Yuan, Cong Wang, Carsten Rudolph, Xiangwen Yang
To avoid the bloated ensemble size during inference, we propose a two-phase defence, in which inference from the Student model is firstly performed to narrow down the candidate differentiators to be assembled, and later only a small, fixed number of them can be chosen to validate clean or reject adversarial inputs effectively.
no code implementations • 9 Jul 2019 • Wen-Bo Xie, Yan-Li Lee, Cong Wang, Duan-Bing Chen, Tao Zhou
Clustering is a fundamental analysis tool aiming at classifying data points into groups based on their similarity or distance.
no code implementations • 17 Feb 2019 • Guang-Yu Nie, Yun Liu, Cong Wang, Yue Liu, Yongtian Wang
Three-dimensional (3-D) scene reconstruction is one of the key techniques in Augmented Reality (AR), which is related to the integration of image processing and display systems of complex information.
no code implementations • 11 Dec 2017 • Yaoguang Li, Wei Cui, Cong Wang
The classification accuracy of electrocardiogram signal is often affected by diverse factors in which mislabeled training samples issue is one of the most influential problems.