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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Congcong Wang Pengyu Liu Kebin Jia Siwei Chen Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

At present, the recognition of weather phenomena mainly depends on the weather sensors and the weather radar. However, large-scale deployment of meteorological observation equipment for intensive weather monitoring is difficult because it is expensive and difficult to maintain. Moreover, convolutional neural networks (CNNs) can also be used to identify weather phenomena, but existing methods require high computing power of equipment, making it difficult to deploy in practice. Therefore, designing a lightweight model that can be deployed in a small device with weak computing power is crucial for intensive weather monitoring. In this paper, we study the shortcomings of some existing lightweight models. By comparing the disadvantages of these models, a new lightweight model is proposed. In addition, considering the number of existing weather datasets are too small to meet real monitoring needs, so we produced a dataset with a more complex variety of weather phenomena. Through the experiments, the proposed method can save more than 25 times memory usage with only 1.55% accuracy lost compared with the best CNNs method which achieves state-of-the-art performance among the other lightweight models.

关键词： Computational modeling Meteorology Task analysis Monitoring Training Atmospheric modeling Convolutional neural networks

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Taxi Drivers' Smoking Behavior Detection in Traffic Monitoring Video

Taxi Drivers' Smoking Behavior Detection in Traffic Monitori...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Siwei Chen Kebin Jia Pengyu Liu Xunping Huang Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing China

ISBN: (数字)9781728132488

ISBN: (纸本)9781728132495

Taxi is an indispensable part of the urban public transportation industry. However, the existence of illegal operating behaviors brings security risks to passengers and affects the city's civilization. The paper studies the detection methods of taxi drivers' smoking behavior during operation in the surveillance video environment. Firstly, the Vibe algorithm is used to detect the motion foreground of the video. Then the Haar-Adaboost algorithm is used to identify the taxi and extract the target detection area. The HSV color model is used to extract the color characteristics of the smoking smoke, and separate the target area from the moving objects which is similar to smoking smoke. Finally, combined changes in shape and movement characteristics of smoking smoke to further eliminate the interference objects, and the final detection results are obtained. The experimental results show that this algorithm has high realtime and accuracy, which is beneficial to off-site law enforcement in intelligent traffic management.

关键词： Public transportation Feature extraction Object detection Image color analysis Surveillance Law enforcement Heuristic algorithms

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An Improvement for View Synthesis Optimization Algorithm 12th

An Improvement for View Synthesis Optimization Algorithm

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12th International Conference on Genetic and Evolutionary computing, ICGEC 2018

作者： Liu, Chang Jia, Kebin Liu, Pengyu Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Laboratory of Advanced Information Networks Beijing100124 China Beijing Advanced Innovation Center for Future Internet Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University of Technology Beijing100124 China

ISBN: (纸本)9789811358401

View synthesis optimization (VSO) allows 3D video system to improve the quality of synthesized views (SVs). Based on the latest segment-based VSO scheme, we find that not all of the intra mode and skip interval are necessary to be considered. Therefore, in this paper, an early determination of intra mode and optimal skip interval based on VSO scheme in 3D-HEVC is presented. First, we discuss a measure to select the best intra mode. Then, we decide the optimal skip interval based on statistical analysis. Experimental results indicate that the proposed algorithm achieves a reduction of 21.711% with negligible loss in rate-distortion performance compared with the original 3D-HEVC encoder, and the encoding time has also reduced to 7.869% compared with the others. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Electric distortion

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Let's play music: Audio-driven performance video generation

arXiv

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arXiv 2020年

作者： Zhu, Hao Li, Yi Zhu, Feixia Zheng, Aihua He, Ran Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei China CASIA Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology CAS Beijing China

We propose a new task named Audio-driven Performance Video Generation (APVG), which aims to synthesize the video of a person playing a certain instrument guided by a given music audio clip. It is a challenging task to generate the high-dimensional temporal consistent videos from low-dimensional audio modality. In this paper, we propose a multistaged framework to achieve this new task to generate realistic and synchronized performance video from given music. Firstly, we provide both global appearance and local spatial information by generating the coarse videos and keypoints of body and hands from a given music respectively. Then, we propose to transform the generated keypoints to heatmap via a differentiable space transformer, since the heatmap offers more spatial information but is harder to generate directly from audio. Finally, we propose a Structured Temporal UNet (STU) to extract both intra-frame structured information and inter-frame temporal consistency. They are obtained via graph-based structure module, and CNN-GRU based high-level temporal module respectively for final video generation. Comprehensive experiments validate the effectiveness of our proposed framework. Copyright © 2020, The Authors. All rights reserved.

关键词： Music

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Epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China:a hospital-based retrospective study

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Neural Regeneration Research 2024年第5期19卷 1126-1132页

作者： Hengxing Zhou Yongfu Lou Lingxiao Chen Yi Kang Lu Liu Zhiwei Cai David BAnderson Wei Wang Chi Zhang Jinghua Wang Guangzhi Ning Yanzheng Gao Baorong He Wenyuan Ding Yisheng Wang Wei Mei Yueming Song Yue Zhou Maosheng Xia Huan Wang Jie Zhao Guoyong Yin Tao Zhang Feng Jing Rusen Zhu Bin Meng Li Duan Zhongmin Zhang Desheng Wu Zhengdong Cai Lin Huang Zhanhai Yin Kainan Li Shibao Lu Shiqing Feng Department of Orthopedics The Second HospitalCheeloo College of MedicineShandong UniversityShandongChina Department of Orthopedics Shandong University Center for OrthopedicsQilu HospitalCheeloo College of MedicineShandong UniversityShandongChina Department of Orthopedics Tianjin Medical University General HospitalInternational Science and Technology Cooperation Base of Spinal Cord InjuryTianjin Key Laboratory of Spine and Spinal CordTianjinChina Faculty of Medicine and Health The Back Pain Research TeamSydney Musculoskeletal HealthThe Kolling InstituteUniversity of SydneySydneyNSWAustralia Department of Spine Surgery Honghui HospitalXi’an Jiaotong UniversityXi’anShaanxi ProvinceChina Department of Burns and Plastic Surgery The Fourth Medical Center of Chinese PLA General HospitalBeijingChina Faculty of Medicine and Health School of Health SciencesUniversity of SydneyNSWAustralia Sydney Spine Institute BurwoodSydneyNSWAustralia Laboratory of Epidemiology Tianjin Neurological InstituteDepartment of NeurologyTianjin Medical University General Hospital&Tianjin Neurological InstituteKey Laboratory of Post-Neuroinjury Neuro-repair and Regeneration in Central Nervous SystemMinistry of Education and Tianjin CityTianjinChina Department of Orthopedics Henan Provincial People’s HospitalZhengzhouHenan ProvinceChina Department of Spinal Surgery The Third Hospital of Hebei Medical UniversityShijiazhuangHebei ProvinceChina Department of Orthopedics The First Affiliated Hospital of Zhengzhou UniversityZhengzhouHenan ProvinceChina Department of Spine Surgery Zhengzhou Orthopedics HospitalZhengzhouHenan ProvinceChina Department of Orthopedic Surgery and Orthopedic Research Institute West China HospitalSichuan UniversityChengduSichuan ProvinceChina Department of Orthopedics Xinqiao HospitalArmy Medical UniversityChongqingChina Department of Orthopedics The First Affiliated Hospital of China Medical UniversityShenyangLiaoning ProvinceChina Department of Spinal Surgery Shengj

Traumatic spinal cord injury is potentially catastrophic and can lead to permanent disability or even *** has the largest population of patients with traumatic spinal cord *** studies of traumatic spinal cord injury in China have mostly been regional in scope;national-level studies have been *** the best of our knowledge,no national-level study of treatment status and economic burden has been *** retrospective study aimed to examine the epidemiological and clinical features,treatment status,and economic burden of traumatic spinal cord injury in China at the national *** included 13,465 traumatic spinal cord injury patients who were injured between January 2013 and December 2018 and treated in 30 hospitals in 11 provinces/municipalities representing all geographical divisions of *** epidemiological and clinical features,treatment status,and total and daily costs were *** in the percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department and cost of care were assessed by annual percentage change using the Joinpoint Regression *** percentage of traumatic spinal cord injuries among all hospitalized patients and among patients hospitalized in the orthopedic department did not significantly change overall(annual percentage change,-0.5%and 2.1%,respectively).A total of 10,053(74.7%)patients underwent *** 2.8%of patients who underwent surgery did so within 24 hours of injury.A total of 2005(14.9%)patients were treated with high-dose(≥500 mg)methylprednisolone sodium succinate/methylprednisolone(MPSS/MP);615(4.6%)received it within 8 *** total cost for acute traumatic spinal cord injury decreased over the study period(-4.7%),while daily cost did not significantly change(1.0%increase).Our findings indicate that public health initiatives should aim at improving hospitals’ability to complete early surgery within 24 ho

关键词： China clinical features costs epidemiology methylprednisolone sodium succinate methylprednisolone retrospective study traumatic spinal cord injury treatment

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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Information Technology,Big Data and Artificial intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Xianzhi Qi Wenxing Fu Pei An Bingli Wu Jie Ma National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781728152240

ISBN: (纸本)9781728152257

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy.

关键词： Three-dimensional displays Laser radar Filtering Filtering algorithms Spatial resolution Task analysis Measurement by laser beam

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Controllability of Indu-Bala product networks

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Neural Networks 2025年 190卷 107622页

作者： Zhang, Qiang Huang, Junjie Liu, Bo Su, Housheng Chen, Alatancang School of Mathematical Sciences Inner Mongolia University Hohhot010021 China School of Information Engineering Minzu University of China Beijing100081 China National Key Laboratory of Multispectral Information Intelligent Processing Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Mathematical Sciences the Ministry of Education Key Laboratory for Infinite-dimensional Hamiltonian System and Its Algorithm Application Inner Mongolia Normal University Hohhot010022 China

A composite network formed by factor networks is a new type of complex network model that can describe different types of agents and multiple complicated relationships in complex systems. "Indu-Bala product" of graphs is a new graph operation with symmetry properties and good mathematical expression, which enables one to construct many pairs of respective co-spectral graphs. This work studies the controllability of a composite network formed by factor networks via Indu-Bala product based on Laplacian dynamics. The eigenvalues and eigenvectors of Indu-Bala product networks (IBPNs) can be represented by factors’ eigenvalues and eigenvectors, which can reduce the computational complexity and analytical burden. Based on the PBH test, sufficient and necessary algebraic criterions for controllability of IBPNs are established, which reveal the controllability relationship between entire network and its factors. This work will help one to construct, understand and improve the composite complex network models, and gain insight into the synergistic mechanisms of the networks. © 2025 Elsevier Ltd

关键词： Eigenvalues and eigenfunctions

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Relative Pose Estimation of Visual SLAM Based on Convolutional Neural Networks

Relative Pose Estimation of Visual SLAM Based on Convolution...

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第三十八届中国控制会议

作者： Xiaogang Ruan Fei Wang Jing Huang Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

Pose estimation is the core module of the visual SLAM system, which is usually calculated by the front-end visual odometry. The calculated pose gives the initial estimation of the camera pose that is the basis for later map construction and path planning. The target of pose estimation is to calculate the relative motion between two frames. The absolute pose of the latter frame can be calculated according to the absolute pose of the previous frame and the relative transformation matrix of the two frames. The main methods for calculating the relative motion of two frames are feature-based method and direct method, and both of them have been successfully applied in various visual SLAM systems. But they all have the disadvantage of needing to carefully adjust the parameters, and sensitive to environment and illumination changes, image blur and other factors. With the great success of deep learning in the field of computer vision, researchers began to explore the use of deep learning methods to solve pose estimation problems. This paper proposes a neural network model for calculating the relative motion of two *** training and testing are carried out on a public dataset. The experimental results show that the model shows good performance for known scenes and has certain generalization ability for unknown environments, proving that deep learning methods have the potential to solve the problem of pose estimation.

关键词： pose estimation deep learning CNN SLAM

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Visual Loop Closure Detection Based on Stacked Convolutional and Autoencoder Neural Networks

Visual Loop Closure Detection Based on Stacked Convolutional...

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第二届先进电子材料、计算机与材料工程国际学术会议（AEMCME 2019）

作者： Fei Wang Xiaogang Ruan Jing Huang Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

Simultaneous localization and mapping is the basis for solving the problem of robotic autonomous movement. Loop closure detection is vital for visual simultaneous localization and mapping. Correct detection of closed loops can effectively reduce the accumulation error of the robot poses, which plays an important role in building a globally consistent environment map. Traditional loop closure detection adopts the method of extracting handcrafted image features, which are sensitive to dynamic environments and are poor in robustness. In this paper, a method called stacked convolutional and autoencoder neural networks is proposed to automatically extract image features and perform dimensionality reduction processing. These features have multiple invariances in image transformation. Therefore, this method is robust to environmental changes. Experiments on public datasets show that the proposed method is superior to traditional methods in terms of accuracy, recall, and average accuracy, thereby validating the effectiveness of the proposed method.

关键词：

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A PSO-RRBF neural network for BOD prediction in sewage treatment

A PSO-RRBF neural network for BOD prediction in sewage treat...

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第三十八届中国控制会议

作者： Minghui Chu Wenjing Li Junfei Qiao Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System

Aiming at the question that the effluent biochemical oxygen demand(BOD)in sewage treatment is difficult to measure accurately in real time,a soft-measurement model of recursive radial basis function(RRBF)neural network based on PSO algorithm(PSO-RRBF)is proposed to predict the effluent ***,the PSO algorithm is put forward to determine not only the input variables but also the structure of the RRBF ***,the gradient descent method is used to adjust the weights,center and ***,the soft-measurement model is applied to the actual sewage treatment *** experimental results show that the soft-measurement model has a more compact structure and its accuracy is improved compared with other models.

关键词： PSO algorithm recursive RBF gradient descent method effluent BOD soft measurement

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