2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)最新文献

Efficiency of Cooperation between Human and Remote Robot System with Force Feedback* 基于力反馈的人机协作效率研究*

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-11-14 DOI: 10.1109/IISR.2018.8535914

Yuichi Toyoda, Pingguo Huang, Y. Ishibashi, Y. Tateiwa, Hitoshi Watanabe

引用次数: 2

A High Speed VLSI Implementation of 256-bit Scalar Point Multiplier for ECC over GF (p) 基于GF (p)的256位标量点乘法器的高速VLSI实现

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535680

Jianwei Liu, Zhenyu Guan, Dongxu Cheng, Ziyu Wang

{"title":"A High Speed VLSI Implementation of 256-bit Scalar Point Multiplier for ECC over GF (p)","authors":"Jianwei Liu, Zhenyu Guan, Dongxu Cheng, Ziyu Wang","doi":"10.1109/IISR.2018.8535680","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535680","url":null,"abstract":"With the rapid development of cloud computing, e-commerce, authentication among multi-robot systems, the highspeed implementation of Elliptic Curve Cryptography (ECC) is in widespread use. The performance of ECC is decided by the design of scalar point multiplier, which is one of the most time-consuming component. This paper presents a full set of methods to achieve an ultra high-speed scalar point multiplier, its Scalar Point Multiplication (SPM) is optimized comprehensively in terms of speed-first design approach by concurrently implementing the Point-add (PA) and Point-double (PD) algorithms, improving large integer modular inversion algorithm and large integer modular multiplication algorithm. Finally, Montgomery domain operation and Non-Adjacent Form (NAF) encoding theory are applied to enhance the speed of scalar point multiplier. In the VLSI design, a high-speed $pmb{256times 256}$ -bit scalar point multiplier is achieved based on SMIC's 65nm process. It can complete single calculation of SPM within 12.5us on average, in other word, 80,000 times of SPM can be computed in one second. Compared to the scalar point multiplier realized by other publications based on VLSI, the reports for circuits synthesis show that our multiplier is optimal in terms of $AT^{2}$ and ultrafast in terms of speed.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124284081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A New Risk Assessment Method for Surface Vessels 一种新的水面船舶风险评估方法

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535891

Kai Zheng, Yabo Chen, Yi Jiang

引用次数: 0

Research on Motion Algorithm for Intelligent Operation of Rock Drill With Eight Degrees of Freedom 八自由度凿岩机智能作业运动算法研究

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535962

Yundou Xu, S. Tong, Zhongjin Ju, Zengzhao Wang, Yunfeng Zhao, Jiantao Yao, Yongsheng Zhao

引用次数: 0

The Study of Facial Gesture Based on Facial Features 基于面部特征的面部手势研究

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535785

Kun Yu, Jibin Yin

引用次数: 4

Dynamics Modeling of Human Elbow Joint for Intelligent Training 面向智能训练的人体肘关节动力学建模

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535760

Yong Li, Dongzhen Zhai, Baiqing Sun, Junyou Yang

引用次数: 0

EMG Classification by using Swarm Intelligence for Myoelectric Prosthetic Hand 基于群体智能的肌电假手肌电信号分类

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535633

Yuki Kuroda, Shunta Togo, Yinlai Jiang, H. Yokoi

引用次数: 0

Development of Myoelectric Prosthetic Hand Control System Using Mobile Terminal 基于移动终端的肌电假肢手控制系统的开发

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535863

T. Harada, Shunta Togo, Yinlai Jiang, H. Yokoi

引用次数: 1

The Design of Wearable Wireless Inertial Measurement Unit for Body motion Capture System 人体运动捕捉系统中可穿戴无线惯性测量单元的设计

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535742

Rongkai Liu, Liang Peng, Lina Tong, Kaizhi Yang, Bingyang Liu

引用次数: 10

The Research of Single-Sample Face Recognition Based on Wavelet Image Fusion 基于小波图像融合的单样本人脸识别研究

2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR) Pub Date : 2018-08-01 DOI: 10.1109/IISR.2018.8535690

Li Ke, Xiangmin Chen, Qiang Du

{"title":"The Research of Single-Sample Face Recognition Based on Wavelet Image Fusion","authors":"Li Ke, Xiangmin Chen, Qiang Du","doi":"10.1109/IISR.2018.8535690","DOIUrl":"https://doi.org/10.1109/IISR.2018.8535690","url":null,"abstract":"As an important part of robot and human-computer interaction, face recognition technology can improve the service and security of robot. In recent years, face recognition technology has improved a lot. Now researchers mainly pay attention to study multi-pose and multi-sample face recognition, but it's difficult to get the method of obtaining these images. However, it is easy to get single face image of per person. So, it is very significant to study the face recognition with single training sample. This paper introduces the single-sample face recognition research based on wavelet image fusion. Firstly, it uses the methods of wavelet transformation and image fusion to obtain the low frequency information of registered image and deposit it to library. Then fusing the low frequency information in library and the high frequency information in tested images. By computing the Euclidean distances between these two images and take it as the input feature to the nerve network to classify. Also, it will use BP neural network to make up the classifier of face recognition and improve it based on traditional neural network. Single face image will be designed matched to every face, activation functions and nodes of nerve cells of the input layer, hidden layer and output layer are designed actively. Lastly through the experiments on the face detection of FERET base, the result is found that the classifier designed in this article is useful for the detection and recognition of human faces with perspective angles, ornaments and in different sizes.","PeriodicalId":201828,"journal":{"name":"2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130952504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2