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IEEE International Conference on Robotics and Biomimetics

作者： De-Xing Huang Xiao-Hu Zhou Xiao-Liang Xie Shi-Qi Liu Zhen-Qiu Feng Jian-Long Hao Zeng-Guang Hou Ning Ma Long Yan The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China The School of Information Shanxi University of Finance and Economics Taiyuan China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing China The Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology Taipa Macau The Department of Interventional Neuroradiology Beijing Tiantan Hospital Capital Medical University Beijing China

ISBN: (纸本)9781665481106

2D/3D medical image registration of pre-operative volumes and intra-operative images plays an important role in neurological interventions. However, vast space of transformation parameters makes this task incredibly challenging. In this paper, a novel two-stage framework for 2D/3D registration is proposed. It consists of two basic modules: CNN regression for preliminarily estimating transformation parameters, and centroid alignment for further reducing estimation errors to get refined images. Experimental results on two patients show the proposed framework can achieve superior performances to baseline methods with an inference rate of 22 FPS, satisfying real-time requirements (6~12 FPS) in clinical practice. Extensive ablation studies prove the effectiveness of centroid alignment in significantly improving registration accuracies. These promising results indicate the framework has the potential to be integrated into navigation frameworks for neurological interventions, facilitating treatments of physicians.

关键词： Image registration Estimation error Three-dimensional displays Navigation Biomimetics Medical services Real-time systems

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The manufacturing procedure of 3D printed models for endoscopic endonasal transsphenoidal pituitary surgery

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TECHNOLOGY AND HEALTH CARE 2020年第S1期28卷 S131-S150页

作者： Shen, Zhen Xie, Yi Shang, Xiuqin Xiong, Gang Chen, Shi Yao, Yong Pan, Zhouxian Pan, Hui Dong, Xisong Li, Yuqing Guo, Chao Wang, Fei-Yue Chinese Acad Sci Beijing Engn Res Ctr Intelligent Syst & Technol Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Shandong Peoples R China Chinese Acad Sci Guangdong Engn Res Ctr 3D Printing & Intelligent Cloud Comp Ctr Dongguan 523808 Guangdong Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Dept Endocrinol Peking Union Med Coll Hosp Key Lab EndocrinolNatl Hlth Commiss Beijing 100730 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Dept Neurosurg Peking Union Med Coll Hosp Beijing 100730 Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Dept Allergy Peking Union Med Coll Hosp Beijing 100730 Peoples R China Univ Southern Calif Viterbi Sch Engn Los Angeles CA 90089 USA Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 101408 Peoples R China

BACKGROUND: Endoscopic endonasal transsphenoidal pituitary surgery is usually difficult and risky. With limited sources of cadaveric skulls, traditional methods of using virtual images to study the surgery are difficult for neurosurgeons and students because the surgery requires spatial imagination and good understanding of the patient's conditions as well as practical experience. The three-dimensional (3D) printing technique has played an important role in clinical medicine due to its advantages of low cost, high-efficiency and customization. OBJECTIVE: CT images are used as the source data of 3D printing. The data obtained directly from the CT machine has limited accuracy, which cannot be printed without processing. Some commercial platforms can help build an accurate model but the cost and customization are not satisfactory. In this situation, a tactile, precise and low-cost 3D model is highly desirable. METHODS: Three pieces of computer software are used in the manufacturing of medical 3D models and the processing procedure is easy to understand and operate. RESULTS: This study proposes a practical and cost-effective method to obtain the corrected digital model and produce the 3D printed skull with complete structures of the nasal cavity, sellar region and different levels of pituitary tumors. The model is used for the endoscopic endonasal transsphenoidal pituitary surgery preparation. CONCLUSION: The 3D printed medical model can directly help neurosurgeons and medical students to practice their surgery skills on both general and special cases with customized structures and different levels of tumors.

关键词： Endoscopic endonasal transsphenoidal pituitary surgery 3D printing surgery simulation pituitary tumor

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Scene-specific pedestrian detection based on parallel vision

arXiv

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arXiv 2017年

作者： Zhang, Wenwen Wang, Kunfeng Qu, Hua Zhao, Jihong Wang, Fei-Yue School of Software Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266000 China School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Communication and Information Engineering Xi’an Jiaotong University Xi’an710049 China Research Center for Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

As a special type of object detection, pedestrian detection in generic scenes has made a significant progress trained with large amounts of labeled training data manually. While the models trained with generic dataset work bad when they are directly used in specific scenes. With special viewpoints, flow light and backgrounds, datasets from specific scenes are much different from the datasets from generic scenes. In order to make the generic scene pedestrian detectors work well in specific scenes, the labeled data from specific scenes are needed to adapt the models to the specific scenes. While labeling the data manually spends much time and money, especially for specific scenes, each time with a new specific scene, large amounts of images must be labeled. What’s more, the labeling information is not so accurate in the pixels manually and different people make different labeling information. In this paper, we propose an ACP-based method, with augmented reality’s help, we build the virtual world of specific scenes, and make people walking in the virtual scenes where it is possible for them to appear to solve this problem of lacking labeled data and the results show that data from virtual world is helpful to adapt generic pedestrian detectors to specific scenes. Copyright © 2017, The Authors. All rights reserved.

关键词： Virtual reality

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A right-of-way based strategy to implement safe and efficient driving at non-signalized intersections for automated vehicles

arXiv

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arXiv 2019年

作者： Xing, Yadong Zhao, Can Li, Zhiheng Zhang, Yi Li, Li Wang, Fei-Yue Wang, Xiao Wang, Yujing Su, Yuelong Cao, Dongpu Department of Automation Tsinghua University Beijing100084 China Graduate School at Shenzhen Tsinghua University Shenzhen518055 China Department of Automation BNRist Tsinghua University Beijing100084 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Traffic Management Solution Division AutoNavi Software Co Beijing100102 China Driver Cognition and Automated Driving Laboratory University of Waterloo WaterlooN2L 3G1 Canada

Non-signalized intersection is a typical and common scenario for connected and automated vehicles (CAVs). How to balance safety and efficiency remains difficult for researchers. To improve the original Responsibility Sensitive Safety (RSS) driving strategy on the non-signalized intersection, we propose a new strategy in this paper, based on right-of-way assignment (RWA). The performances of RSS strategy, cooperative driving strategy, and RWA based strategy are tested and compared. Testing results indicate that our strategy yields better traffic efficiency than RSS strategy, but not satisfying as the cooperative driving strategy due to the limited range of communication and the lack of long-term planning. However, our new strategy requires much fewer communication costs among vehicles. Copyright © 2019, The Authors. All rights reserved.

关键词： Vehicles

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Transportation 5.0: The DAO to Safe, Secure, and Sustainable Intelligent Transportation systems

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION systems 2023年第10期24卷 10262-10278页

作者： Wang, Fei-Yue Lin, Yilun Ioannou, Petros A. Vlacic, Ljubo Liu, Xiaoming Eskandarian, Azim Lv, Yisheng Na, Xiaoxiang Cebon, David Ma, Jiaqi Li, Lingxi Olaverri-Monreal, Cristina Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Macau Peoples R China Urban Comp Lab Shanghai 200232 Peoples R China Shanghai Artificial Intelligence Lab Shanghai 200232 Peoples R China Univ Southern Calif Dept Elect Engn Syst Los Angeles CA 90007 USA Griffith Univ Inst Intelligent & Integrated Syst Nathan Qld 4111 Australia Griffith Univ Sch Engn & Built Environm Nathan Qld 4111 Australia Beijing Univ Technol Coll Metropolitan Transportat Beijing 100081 Peoples R China Dept Mech Engn Virginia Tech Blacksburg VA 24061 USA Chinese Acad Sci Inst Automat Beijing 100045 Peoples R China Univ Cambridge Dept Engn Cambridge CB2 1TN England Univ Calif Los Angeles Samueli Sch Engn Los Angeles CA 90095 USA Indiana Univ Purdue Univ Indianapolis IUPUI Purdue Sch Engn & Technol Dept Elect & Comp Engn Indianapolis IN 46202 USA Johannes Kepler Univ Linz Dept Intelligent Transportat Syst A-4040 Linz Austria

In 2014, IEEE Intelligent Transportation systems Society established a Technical Committee on Transportation 5.0 with the mission of promoting and transforming the deployment of advanced and innovative technologies, especially Artificial Intelligence in transportation. This paper briefly summarizes our main research and findings over the last decade. Transportation Foundation Models, Transportation Scenarios Engineering, and Transportation Operating systems have been identified as the main directions for the research and development of next-generation intelligent transportation systems.

关键词： Intelligent transportation systems cyber-physical-social systems parallel intelligence knowledge automation DAOs transportation 5.0

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Large scale online kernel learning

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Jing Lu Steven C. H. Hoi Jialei Wang Peilin Zhao Zhi-Yong Liu Google MPI for Intelligent Systems School of Information Systems Singapore Management University Singapore Department of Computer Science University of Chicago Chicago IL Institute for Infocomm Research A*STAR Connexis Singapore State Key Lab of Management and Control for Complex System Chinese Academy of Sciences Beijing China

In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.

关键词： kernel approximation large scale machine learning online learning

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Path Planning System for Smart Cars Used in Education

Path Planning System for Smart Cars Used in Education

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Guangyu Xiong Lulu Niu Yanfu Tian Jiehan Zhou Babak Mohajeri Timo R. Nyberg Silk Road Business School Sanya University(USY) China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing The Cloud Computing Center Chinese Academy of Sciences Dongguan China School of Articial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Oulu Oulu Finland Aalto University Espoo Finland

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

In this paper, we developed a path planning system for smart cars for teaching electronic engineering or computer science, which consists of the interactive platform for smart cars development and path planning. Designed by Visual C++, the interactive platform can call Matlab engine, allows users to choose path optimization algorithms such as genetic or A-star(A*) algorithm for different tasks and control smart cars through serial ports. The simulation and practice demonstrate that our interactive platform can help learners to plan paths and control intelligent vehicles without specially designing a user interface.

关键词： Education Path planning Automobiles Task analysis Optimization Programming profession Matlab

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Trends in the manifestations of 9754 gout patients in a Chinese clinical center: A 10-year observational study

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JOINT BONE SPINE 2021年第6期88卷 105078-105078页

作者： Gao, Qianhui Cheng, Xiaoyu Merriman, Tony R. Wang, Can Cui, Lingling Zhang, Hui Sun, Wenyan Wang, Jing Wang, Feiyue Li, Changgui Lu, Jie Qingdao Univ Affiliated Hosp Dept Endocrinol & Metab Shandong Prov Key Lab Metab Dis Qingdao 266003 Peoples R China Qingdao Univ Affiliated Hosp Dept Endocrinol & Metab Qingdao Key Lab Gout Qingdao 266003 Peoples R China Qingdao Univ Inst Metab Dis Qingdao 266003 Peoples R China Univ Otago Dept Biochem Dunedin New Zealand Univ Alabama Birmingham Div Clin Immunol & Rheumatol Birmingham AL 35294 USA Qingdao Acad Intelligent Ind Inst Smart Healthcare Syst Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Objective: The prevalence of gout is increasing but studies of its clinical features in large samples are lacking. This study aimed to clarify changes in the clinical manifestations of gout in China over the last decade and investigate the clinical features and risk factors of early-onset gout. Methods: Clinical manifestations were compared between 9754 gout patients who first presented at our clinic with gout in 2008-2012 (earlier group) or 2013-2018 (later group). Gout onset <= 30 years old was defined as early-onset and > 30 years as late-onset. Clinical features and risk factors were compared between the groups. Results: The gout-onset age was 4.14 years younger and the percentage of early-onset gout (3827 patients) was higher in the later 2013-2018 group (5979 patients). The disease duration was significantly shorter (5.72 +/- 0.09 vs. 6.01 +/- 0.11 years P < 0,05) and the ratio of patients with tophi was correspondingly lower in the later group (22.0% vs. 20.0%, P < 0,05). More patients were obese (32.6% vs. 37.7%, P < 0.001) and serum urate levels (465.0 +/- 1.9 mu mol/L vs. 485.5 +/- 1.5 mu mol/L) were significantly higher in the later group. As the age of gout-onset became younger, we did the multivariate logistic regression and identified a positive family history, male sex, obesity, elevated serum urate, and sugar-sweetened soft drinks as independent predictors of early-onset gout. Conclusion: The manifestations of gout in China have changed over the last decade, associated with trend towards younger onset. (C) 2020 The Authors. Published by Elsevier Masson SAS on behalf of Societe francaise de rhumatologie. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/)

关键词： Gout Early-onset Risk factors

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Deep Rank-Consistent Pyramid Model for Enhanced Crowd Counting

arXiv

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arXiv 2022年

作者： Gao, Jiaqi Huang, Zhizhong Lei, Yiming Shan, Hongming Wang, James Z. Wang, Fei-Yue Zhang, Junping The Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai200433 China The Institute of Science and Technology for Brain-inspired Intelligence MOE Frontiers Center for Brain Science Fudan University Shanghai200433 China The Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai201210 China The College of Information Sciences and Technology The Pennsylvania State University University ParkPA16802 United States The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Institute of Systems Engineering Macau University of Science and Technology China Qingdao Academy of Intelligent Industries Qingdao266109 China

Most conventional crowd counting methods utilize a fully-supervised learning framework to establish a mapping between scene images and crowd density maps. They usually rely on a large quantity of costly and time-intensive pixel-level annotations for training supervision. One way to mitigate the intensive labeling effort and improve counting accuracy is to leverage large amounts of unlabeled images. This is attributed to the inherent self-structural information and rank consistency within a single image, offering additional qualitative relation supervision during training. Contrary to earlier methods that utilized the rank relations at the original image level, we explore such rank-consistency relation within the latent feature spaces. This approach enables the incorporation of numerous pyramid partial orders, strengthening the model representation capability. A notable advantage is that it can also increase the utilization ratio of unlabeled samples. Specifically, we propose a Deep Rank-consistEnt pyrAmid Model (DREAM), which makes full use of rank consistency across coarse-to-fine pyramid features in latent spaces for enhanced crowd counting with massive unlabeled images. In addition, we have collected a new unlabeled crowd counting dataset, FUDAN-UCC, comprising 4,000 images for training purposes. Extensive experiments on four benchmark datasets, namely UCF-QNRF, ShanghaiTech PartA and PartB, and UCF-CC-50, show the effectiveness of our method compared with previous semi-supervised methods. The codes are available at https://***/bridgeqiqi/DREAM. Copyright © 2022, The Authors. All rights reserved.

关键词： Image enhancement

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FusionPlanner: A Multi-task Motion Planner for Mining Trucks via Multi-sensor Fusion

arXiv

引用

arXiv 2023年

作者： Teng, Siyu Li, Luxi Li, Yuchen Hu, Xuemin Li, Lingxi Ai, Yunfeng Chen, Long Department of Computer Science Hong Kong Baptist University Hong Kong Department of Computer Science BNU-HKBU United International College Zhuhai China The School of Artificial Intelligence Hubei University Wuhan China Waytous Inc. Haidian Distinct Beijing China Indianapolis United States School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China

In recent years, significant achievements have been made in motion planning for intelligent vehicles. However, as a typical unstructured environment, open-pit mining attracts limited attention due to its complex operational conditions and adverse environmental factors. A comprehensive paradigm for unmanned transportation in open-pit mines is proposed in this research. Firstly, we propose a multi-task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi-sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation. Then, we develop a novel benchmark called MiningNav, which offers three validation approaches to evaluate the trustworthiness and robustness of well-trained algorithms in transportation roads of open-pit mines. Finally, we introduce the Parallel Mining Simulator (PMS), a new high-fidelity simulator specifically designed for open-pit mining scenarios. PMS enables the users to manage and control open-pit mine transportation from both the single-truck control and multi-truck scheduling perspectives. The performance of FusionPlanner is tested by MiningNav in PMS, and the empirical results demonstrate a significant reduction in the number of collisions and takeovers of our planner. We anticipate our unmanned transportation paradigm will bring mining trucks one step closer to trustworthiness and robustness in continuous round-the-clock unmanned transportation. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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