检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Dynamic obstacle tracking based on high-definition map in urban scene

Dynamic obstacle tracking based on high-definition map in ur...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Li, Yuxiao Wang, Can Su, Zhilong Duan, Shengcai Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Beijing100049 China Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781728163215

The application of High-Definition map can realize centimeter-level position in urban scenes, the development of deep learning has made great breakthrough in the point cloud dynamic obstacle recognition. All these technologies make obstacle detection and tracking based on High-Definition map effectively realize in the modern smart city scene. It is different from the previous obstacle detection and tracking methods based purely on vision the using of High-Definition map can provide high-precision positioning and reduce the difficulty of point cloud classification. The using of lidar also solves the problem of up-to-scale in dynamic detection. In this paper, we put forward a new Multi-camera Lidar Point Cloud Map, we complete the map at normal speed on the highway and get a satisfactory result. At the same time, we also find a robust combination of traditional kalman filter, Hungary algorithm and current deep learning to solve dynamic obstacle tracking and detection. The experimental results show that our system can effectively complete the special problem of generating map and target tracking on urban scene. © 2019 IEEE.

关键词： Optical radar

来源：评论

学校读者我要写书评

暂无评论

A lightweight soft exoskeleton in lower limb assistance

A lightweight soft exoskeleton in lower limb assistance

引用

Chinese Automation Congress (CAC)

作者： Yu Zhang Zhuo Wang Chunjie Chen Tao Fang Ruimei Sun Yanjie Li School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China ShenZhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China BeiJing Aerospace Wanyuan Science Technology Co. Ltd. Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

The soft exoskeleton is a wearable robot which is functioned to improve the capacity of human walking or loading. The metabolic of human is increase with the additional load, one integrated design method is used to reduce this effect in this paper. Meanwhile, in order to enhance the convenience and decrease the disturbance to wearer, the wireless module is used to replace the signal line. The nonlinear characteristics and uncertainty of flexible material make the control of soft exoskeleton system be a challenge, a switching controller is proposed to deal with this problem in this paper. It consists of Iterative learning control (ILC) based stable controller and admittance control based unstable controller, functioned with wearers walking stable and not. An experiment of force tracking is conducted to verify the controller performance in this paper, and the result demonstrate that the tracking is well after 20 iteration. In order to evaluate the performance of assistance of soft exoskeleton, five health adult male take part in metabolic experiment By compare the metabolic rate between the wear soft exoskeleton and not wear, the metabolic rate are decrease 7.33%, 14.56% and 10.45% with the walking speed of 3km/h, 5km/h and 7km/h, which are corresponding absolute values decrease of 0.46W/kg, 1.60W/kg and 1.21W/kg respectively.

关键词： AC motors Mechanical cables Wireless communication Pulleys Microprocessors Micromechanical devices Germanium

来源：评论

学校读者我要写书评

暂无评论

An Image segmentation method by multi-scale local thresholding based on class uncertainty theory

An Image segmentation method by multi-scale local thresholdi...

引用

2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Zhou, Likai Jiang, Yuyang Liang, Guoyuan Wu, Xinyu Zhu, Jiafeng Xiang, Huaikun Shenzhen Institutes of Advanced Technology CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences China School of Automotive and Transportation Engineering Shenzhen Polytechnic Shenzhen Guangdong Province China School of Math Sun Yat-sen University Guangzhou Guangdong Province China

ISBN: (纸本)9781728163215

Image segmentation is one of the most important core technologies in the field of image processing and computer vision, which has lots of applications specifically in medical image analysis. Due to medical imaging mechanism, medical images usually suffer from heavy noises, uneven intensity distribution and fuzzy boundaries between biological tissues. That makes classical segmentation methods based on global or local thresholding difficult to get accurate results. This paper proposes an image segmentation method by multi-scale local thresholding based on class uncertainty theory. Firstly, the original image is divided into a set of sub-regions with different scales by using a multi-layer pyramid structure. Secondly, the energy function with inequality constraints is constructed based on class uncertainty and region uniformity. Then by an iterative process, the optimal local threshold for each sub-region are calculated by an optimization algorithm for each layer until the final optimal threshold mask is determined for image segmentation. Experimental results verify that the proposed method can effectively eliminate the interferences caused by image noises, intensity unevenness and fuzzy boundaries, and preserve details of object structure while segmenting the object from the background. Segmentation results demonstrate the superior performance of the proposed method by comparison with supervised range-constrained thresholding methods (RCOtsu), classical global/local Otsu method, and the minimization of homogeneity- and uncertainty-based energy method (MHUE). © 2019 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Improvement of Pose Recognition by Sparse Regularized Convolutional Neural Network

Improvement of Pose Recognition by Sparse Regularized Convol...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Yuan Zhang Xiao Yao Zhongli Wang Hao Su Zihan Yu Guanying Huo Ning Xu Xiaofeng Liu Changzhou Key Laboratory of Robotics and Intelligent Technology College of Internet of Things Engineering Chang Zhou China Electronic and Information Engineering Beijing Jiaotong University Beijing China College of Internet of Things Engineering Chang Zhou China Changzhou Key College of Internet of Things Engineering Changzhou Campus of Hohai University Chang Zhou China

ISBN: (数字)9781728137261

ISBN: (纸本)9781728137278

The paper proposes a method of using deep model (CNN) with sparse regularization term to improve the performance of pose recognition. Convolutional neural network shows its limitations for pose recognition because of its bad convergence. It is believed that the activation function could be simplified by adding the sparseness term. Therefore, we present an algorithm applying the sparse regularization for the deep model with ReLU. Experimental results confirm that the proposed method can accelerate the convergence speed while a high recognition rate maintained.

关键词： Convergence Convolution Convolutional neural networks Training Feature extraction Biological system modeling Pose estimation

来源：评论

学校读者我要写书评

暂无评论

Gaussian curvature filter on 3d mesh

arXiv

引用

arXiv 2020年

作者： Tang, Wenming Gong, Yuanhao Liu, Kanglin Liu, Jun Pan, Wei Liu, Bozhi Qiu, Guoping College of Information Engineering Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Mechanical & Automotive Engineering South China University of Technology Department of Research and Development OPT Machine Vision Tech Co. Ltd Jinsheng Road Changan Dongguan Guangdong523860 China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom

Minimizing Gaussian curvature of meshes is fundamentally important for obtaining smooth and developable surfaces. However, there is a lack of computationally efficient and robust Gaussian curvature optimization method. In this paper, we present a simple yet effective method that can efficiently reduce Gaussian curvature for 3D meshes. We first present the mathematical foundation of our method, which states that for any point on a developable surface there must be another point that lives on its tangent plane. Then, based on this theoretical insight, we introduce a simple and robust implicit Gaussian curvature optimization method named Gaussian Curvature Filter (GCF). GCF implicitly minimizes Gaussian curvature without the need to explicitly calculate the Gaussian curvature itself. GCF is highly efficient and is 20 times faster than the classical standard Gaussian curvature flow method. We present extensive experiments to demonstrate that GCF significantly outperforms state-of-the-art methods in minimizing Gaussian curvature, geometric feature preserving smoothing and mesh noise removal. This method can be used in a large range of applications that involve Gaussian curvature. Copyright © 2020, The Authors. All rights reserved.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

DUE Distribution and Pairing in D2D Communication

DUE Distribution and Pairing in D2D Communication

引用

International Conference on Computer Communications and Networks (ICCCN)

作者： Weifeng Lu Xiaoqiang Ren Jia Xu Siguang Chen Lijun Yang Jian Xu Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China College of IoT Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

The D2D (Device-to-Device) communication has been very popular as it is a promising and low-cost solution to reduce the burden on the cellular network. However, there are rare concerns about the distribution and pairing of DUEs(D2D user equipments), which have a significant impact on QoS (Quality of Service) of D2D communication. In this paper, we propose a novel algorithm based on the coalitional game to optimally adjust the distribution of DUEs. The proposed algorithm aims to form the optimal coalition structure, which achieves a balance between the throughput and power consumption of each coalition, obtaining the enhanced QoS of D2D. We show that our algorithm is superior to the benchmark models in terms of the throughput and energy efficiency of the DUE coalition. To further improve the QoS, we also propose a method to predict and maximize the pairing probability of DUEs. The proposed prediction method adopts the Logistic Regression to model the global pairing probability according to the communication parameters of DUEs. Experimental results show that the proposed prediction method is significantly superior to the benchmark methods in terms of prediction accuracy. In addition, the pairing probability maximization algorithm proposed also significantly improves the pairing probability.

关键词： Device-to-device communication Throughput Power demand Fading channels Games Quality of service Time division multiple access

来源：评论

学校读者我要写书评

暂无评论

Gait Phase Classification Based on sEMG Signals Using Long Short-Term Memory for Lower Limb Exoskeleton Robot

引用

IOP Conference Series: Materials Science and engineering 2020年第1期853卷

作者： Ye Yuan Ziming Guo Can Wang Shengcai Duan Lufeng Zhang Xinyu Wu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences CAS Key Laboratory of Human-Machine Intelligence-Synergic Systems Shenzhen Institutes of Advanced Technology Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University.

In this work, we present a Long Short-Term Memory Model (LSTMM) for gait phase classification based on sEMG signals to control the lower limb exoskeleton robot which can recognize 2 phases (Stand and Swing) of leg phases between the foot and ground. This model only needs four sEMG signals to control the lower limb exoskeleton robot helping the hemiplegia patient walking. Compared with the existing methods, the proposed model not only avoids the complex sensor systems but also enhances the accuracy of gait phase classification. The experimental results first verify the availability of sEMG data acquisition system on the lower limb exoskeleton robot made by the Shenzhen Institutes of Advanced Technologies (SIAT) by quantify the system with gold standard optoelectronic system Vicon, then show that the proposed LSTMM is significantly higher on prediction accuracy and has better robustness for gait phase classification to control the lower limb exoskeleton robot with different speeds. Finally, the maximum accuracy of LSTMM on the gait phase classification is 97.89%.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Interactive Ontology Matching Based on Evolutionary Algorithm

Interactive Ontology Matching Based on Evolutionary Algorith...

引用

International Conference on Computational Intelligence and Security

作者： Xingsi Xue Junfeng Chen Aihong Ren College of Information Science and Engineering Intelligent Information Processing Research Center Fujian Key Lab for Automotive Electronics and Electric Drive Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of IOT Engineering Hohai University ChanZhou China School of Mathematics and Information Science Baoji University of Arts and Sciences Baoji China

ISBN: (数字)9781728160924

ISBN: (纸本)9781728160931

Since different ontologies are mostly developed independently, establishing meaningful links between their entities, so-called ontology matching, is critical to ensure their communication. Due to the complexity of the ontology matching problem, Evolutionary Algorithm (EA) can present a good methodology for determining ontology alignments. However, since none of the similarity measure can distinguish all the identical ontology entities in any context, ontology alignments generated by the automatic matching tools should be validated by the users to ensure their qualities. To improve the quality of the ontology alignment, in this work, a similarity measure is first proposed to calculate the similarity value of two ontology entities; then, an optimal model for ontology matching problem is constructed; after that, an EA-based automatic matcher is presented to solve the ontology matching problem, which can also adaptively determine the timing of getting user involved; and finally, the ontology concept hierarchy graph based reasoning approaches are proposed to tradeoff the user's workload and his work's effect. The experiment is conducted on the Interactive track provided by the Ontology Alignment Evaluation Initiative (OAEI), and the comparisons with OAEI's participants show the effectiveness of our proposal.

关键词： Ontologies Graph theory Pattern matching Evolutionary computation

来源：评论

学校读者我要写书评

暂无评论

P-12.1: Lighting effects, light distribution matters

引用

SID Symposium Digest of Technical Papers 2019年第S1期50卷

作者： Ling Xia Tingting Zhang Xiaofeng Liu Sylvia C. Pont College of IoT Engineering Hohai University Changzhou Key Laboratory of Robotics and Intelligent Technology Jiangsu Key laboratory of Special Robot Technology Changzhou China Department of Industrial Design Perceptual Intelligence lab Delft University of Technology Delft The Netherlands

The interaction between light and its surroundings (i.e. the geometry and materials) shapes the lighting distribution and determines the appearance of scenes and its visual experiences. In this study, we introduced the concept of light distribution solids by distinguishing luminance distribution solids and illuminance distribution solids. It is helpful to understand the spatial and form-giving lighting effects on objects' appearance. Furthermore, this study together with our previous study (Xia, Pont et al. 2016, Xia, Pont et al. 2016) provide theoretical basis for the exploration of extracting photometry parameters out of HDR panoramic photographs of scenes.

关键词： Lighting effects lighting distribution luminance distribution solids illuminance distribution solids light density light diection light diffuseness HDR panoramic photogrphs

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：