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2021 7th International Conference on Manufacturing Technology and Applied Materials, ICAMMT 2021

作者： Zhang, Bin Lu, Zongxue Wang, Qiang Cui, Shiyi Jia, Guangxin Yang, Jun School of Automation Southeast University 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Lianyungang Jari Automation CO. LTD. Lianyungang222006 China

In this thesis, a control system for a wheel hub machining line based on a Fanuc robot, which includes adopting Siemens 300PLC as the main control unit, performing wheel circumferential positioning and center correction based on vision technology, and controlling the machine tool to perform real-time tool compensation based on the measured data, is researched and designed to achieve fully automatic unmanned wheel processing. © Published under licence by IOP Publishing Ltd.

关键词： Wheels

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A Survey on IMU-and-Vision-based Human Pose Estimation for Rehabilitation 41

A Survey on IMU-and-Vision-based Human Pose Estimation for R...

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第41届中国控制会议

作者： Yuan Niu Jinhua She Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of human pose estimation,the human-pose-estimation method applied in rehabilitation therapy has attracted more and more attention in today's aging *** them,inertial measurement units(IMU) and computer vision are two significant methods for human pose *** mainly pay attention to the application of these two methods in the rehabilitation therapy *** this paper,we first summarize the research status of IMU and computer vision in the field of rehabilitation ***,we find that combining the two methods can produce better ***,the main problems of the current research and possible development directions are identified.

关键词： Human Pose Estimation IMU Computer Vision Rehabilitation Therapy

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A camera calibration method based on scene and human semantics 37

A camera calibration method based on scene and human semanti...

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Shu, Yuan Wang, Yangang Southeast University Chien-Shiung Wu College Nanjing China Southeast University School of Automation Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9781665465366

Camera calibration is an important preliminary for many applications such as 3D reconstruction, motion capture and human-computer interactions. Although great achievements have been made in the past several years, it still remains two main problems. The one is that conventional calibration methods always depend on specific calibration tools (e.g., checkerboard). The other is that the calibration procedure is complex when these methods are used in multi-view large scenarios. In this paper, we propose a camera calibration method which can be applied to large-scale sports scenarios without a special calibration object. To tackle these challenges, our key-idea is to use scene and human semantics detected from RGB images to calibrate the intrinsic and extrinsic parameters of multi-view cameras. We first detect the scene and human keypoints, then the initial camera parameters are calculated with the static scene keypoints and a predefined sports field model. Finally, we combine the scene and human semantics to refine the camera intrinsic and extrinsic parameters. Experimental results demonstrate that our method successfully obtains accurate camera intrinsic and extrinsic parameters for large-scale sports scenarios. © 2022 IEEE.

关键词： Semantics

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Multi-task Learning Based Single Temporal Remote Sensing Image Change Detection 12

Multi-task Learning Based Single Temporal Remote Sensing Ima...

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12th International Conference on Computing and Pattern Recognition, ICCPR 2023

作者： Yang, Peixuan Cao, Yichao Lu, Xiaobo College of Software Engineering Southeast University JiangSu NanJing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education JiangSu NanJing China School of Automation Southeast University JiangSu NanJing China

ISBN: (纸本)9798400707988

Change Detection is a classic and fundamental task in remote sensing(RS), and has accomplish remarkable achievement on bitemporal image based methods. However, bitemporal images are very expensive and needs professional researchers to align and label the paired images. Furthermore, most bitemporal image based methods are only semantic-aware not instance-aware, which indicates these methods only use paired images' semantic information. Thus, we propose a method that only needs unpaired RS images with semantic labels. In this paper, we introduce multi-task learning into change detection progress, which comprises four major parts: Boundary-Aware Module, Contextual-Aware Module, Segmentation Module, Change Detection Module. At first, we construct Boundary-Aware Module and Contextual-Aware Module to extract sharp boundary and dense contextual features. Then we feed the feature maps to Change Detection Module and Segmentation Module to accomplish the subtasks. The comprehensive experiments on a single temporal image dataset demonstrate the efficiency of our approach over other bitemporal image based methods, and the experimental results shows our approach is competitive with other methods while all methods was trained on bitemporal image dataset. © 2023 ACM.

关键词： Change detection

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Forecasting product design time based on Gaussian margin regression

Forecasting product design time based on Gaussian margin reg...

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IEEE 2011 10th International Conference on Electronic measurement and Instruments, ICEMI 2011

作者： Shang, Zhigen Yan, Hongsen School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China Department of Automation Yancheng Institute of Technology Yancheng 224003 China

ISBN: (纸本)9781424481590

In order to obtain a forecast model for product design time from a small data set, Gaussian Margin Regression (GMR) is presented on the basis of combining Gaussian Margin Machines and kernel based regression. Gaussian Margin Regression maintains a Gaussian distribution over weight vectors for kernel based regression. The algorithm is applied to seeking the least information distribution that will make actual value be included in the confidential interval with high probability, and embedded genetic algorithm is presented for choosing its relevant parameters. The results of application in injection mold designs reveal that the time forecast model based on GMR is of feasibility and validity. © 2011 IEEE.

关键词： Product design

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3D face landmarking with denoise auto-encoder networks 11

3D face landmarking with denoise auto-encoder networks

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11th International Conference on Digital Image Processing, ICDIP 2019

作者： Wang, Liang Gai, Shaoyan Guo, Shuai School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Cardiff University CF103AT United Kingdom

ISBN: (数字)9781510630765

ISBN: (纸本)9781510630758

3D Facial landmarking plays an important role on 3D face recognition and face expression recognition. However, the most of methods underperform when faces have occluded region such as hair, glasses or finger. To solve this problem, a coarseto-fine method is proposed, containing several denoising auto-encoder networks (denoted as DANs). DANs not only can recover the lost information but improve the accuracy of landmarking. Tests based on Bosphorus dataset show a 100% of good landmarking under 6mm precision of mean error, which demonstrates that our algorithm achieves the state-of-theart performance. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Statistical tests

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System and walking gait design for hexapod search and rescue robot

System and walking gait design for hexapod search and rescue...

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Chinese Intelligent systems Conference, CISC 2017

作者： Yang-Yang, Chen Yingying, Huang School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China School of Electronic Science and Engineering Southeast University Nanjing2017514 China

ISBN: (纸本)9789811064982

In order to adapt to the complex disaster environment, this paper considers the system design of hexapod search and rescue robot. Such hexapod robot is suitable to different kinds of roads and obstacle, which can avoid to the shortcomings of crawler robots. This hexapod search and rescue robot includes the six foot body, voice modular, obstacle avoidance and remote monitoring function. Based on the relationship between the center of gravity and the supporting polygon, the design of the hexagon robot’s walking gait is presented. The feasibility of the hexapod search and rescue robot is verified by the prototype experiment. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Machine design

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A Semi-Supervised Railway Foreign Object Detection Method Based on GAN 21

A Semi-Supervised Railway Foreign Object Detection Method Ba...

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5th International Conference on Computer Science and Application engineering, CSAE 2021

作者： Chen, Yanqi Tong, Shuzhen Lu, Xiaobo Wei, Yun School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Beijing Mass Transit Railway Operation Corporation Limited Beijing China

ISBN: (纸本)9781450389853

The rapid development of deep learning provides new technical means for railway foreign object detection. However, in practical applications, the datasets of railways with foreign objects are scarce. In order to solve this problem, by improving the loss function and anomaly image evaluation standard, this paper proposes a newsemisupervised anomaly detection method based on GAN (Generative Adversarial Networks). Experiments show that our method can achieve railway foreign object detection without anomaly prior knowledge. Regarding anomaly recognition, a 0.058 AUC (Area Under Curve) and a 6% classification accuracy relative improvement for the railway dataset used in this paper are obtained.. © 2021 Association for Computing Machinery. All rights reserved.

关键词： Generative adversarial networks

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Data-free point cloud network for 3d face recognition

arXiv

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arXiv 2019年

作者： Zhang, Ziyu Da, Feipeng Yu, Yi School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering

Point clouds-based Networks have achieved great attention in 3D object classification, segmentation and indoor scene semantic parsing. In terms of face recognition, 3D face recognition method which directly consume point clouds as input is still under study. Two main factors account for this: One is how to get discriminative face representations from 3D point clouds using deep network;the other is the lack of large 3D training dataset. To address these problems, a data-free 3D face recognition method is proposed only using synthesized unreal data from statistical 3D Morphable Model to train a deep point cloud network. To ease the inconsistent distribution between model data and real faces, different point sampling methods are used in train and test phase. In this paper, we propose a curvatureaware point sampling(CPS) strategy replacing the original furthest point sampling(FPS) to hierarchically downsample feature-sensitive points which are crucial to pass and aggregate features deeply. A PointNet++ like Network is used to extract face features directly from point clouds. The experimental results show that the network trained on generated data generalizes well for real 3D faces. Fine tuning on a small part of FRGCv2.0 and Bosphorus, which include real faces in different poses and expressions, further improves recognition accuracy. Copyright © 2019, The Authors. All rights reserved.

关键词： Face recognition

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Stability analysis on discrete-time Cohen-Grossberg neural networks with bounded distributed delay

Stability analysis on discrete-time Cohen-Grossberg neural n...

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作者： Li, Tao Wang, Ting Fei, Shumin School of Electronic Engineering and Automation Henan Polytechnic University Jiaozuo 454000 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing 210096 China

ISBN: (纸本)9789881725592

This paper investigates the asymptotical stability for discrete-time Cohen-Grossberg neural networks with both timevarying and distributed delays. By constructing a novel Lyapunov-Krasovskii functional and introducing some free-weighting matrices, one delay-dependent sufficient condition is obtained by using convex combination. The criterion is presented in terms of LMIs and the feasibility can be easily checked with the help of LMI in Matlab Toolbox. In addition, the activation function can be described more generally, which generalizes those earlier methods. Finally, the effectiveness of obtained results can be further illustrated by one numerical example in comparison with the existent ones. © 2011 Chinese Assoc of automation.

关键词： Lyapunov functions

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