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检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

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Mapping the surface of an unevenly moving steel billet

Mapping the surface of an unevenly moving steel billet

引用

2005 IEEE international symposium on computational intelligence in robotics and automation CIRA 2005

作者： Terho, Sami Paanajärvi, Janne Visala, Arto Automation Technology Laboratory Helsinki University of Technology P.O.Box 5500 02015 HUT Finland

paper presents a system for measuring three dimensional surface map of steel billets. The proposed system is used for quality control of the surfaces of the billets. The system is based on camera and a laser stripe generator. The billet is moved in front of the inspection system with an external moving mechanism. Triangulation is used for measuring the surface map. The three-dimensional movements of the billet are measured by combining optical flow and information from the laser stripes. © 2005 IEEE.

关键词： Billets (metal bars)

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Adaptive robotics in the entertainment industry

Adaptive robotics in the entertainment industry

引用

2003 IEEE international symposium on computational intelligence in robotics and automation, CIRA 2003

作者： Lund, Henrik Hautop Maersk Mc-Kinney Moller Institute for Production Technology University of Southern Denmark Campusvej 55 Odense M.5230 Denmark

ISBN: (纸本)0780378660

In this paper, I discuss the market for adaptive robots in the entertainment industry, and some of the most promising avenues for the future development of this field. A United Nations report forecast an impressive 800% growth of this industry within 2-3 years. However, there are many issues that has to be considered when entering this field/market. Most notably, robotic toy systems can be developed to become either closed or open systems. Here, I promote open systems based on different psychological considerations, and I describe a few systems that we developed to enlighten the possibilities for open systems. © 2003 IEEE.

关键词： robotics

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SILT: Scale-Invariant Line Transform

SILT: Scale-Invariant Line Transform

引用

IEEE international symposium on computational intelligence in robotics and automation

作者： Khaleghi, Bahador Baklouti, Malek Karray, Fakhreddin O. Univ Waterloo Dept Elect & Comp Engn Pattern Anal & Machine Intelligence Lab Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781424448081

Line matching is useful in many computer vision tasks such as object recognition, image registration, and 3D reconstruction. The literature on line matching has advanced in recent years, nevertheless, compared to other features (such as point and region matching approaches) it has made little progress. Especially, very few algorithms address the problem of image scaling. In this paper, we present a new line detection and matching algorithm that is invariant to image scale variation (SILT). The algorithm detects line segments as local extrema in the scale-space. Each detected line segment is represented in a distinctive manner using Haar-like features. PCA is further deployed to improve upon the compactness and robustness of representation. Experimental results demonstrate the effectiveness of the proposed approach to deal with image scale variations.

关键词： Object recognition

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Data Security Structure of a Students' Attendance Register Based on Security Cameras and Blockchain Technology 22

Data Security Structure of a Students' Attendance Register B...

引用

IEEE Joint 22nd international symposium on computational intelligence and Informatics / 8th IEEE international Conference on Recent Achievements in Mechatronics, automation, Computer Science and robotics (CINTI-MACRo)

作者： Balint, Krisztian Obudai Univ Keleti Karoly Fac Business & Management Inst Enterprise Dev & Infocommun Budapest Hungary

ISBN: (纸本)9798350398823

The latest, modern security camera systems record numerous data at once. With the utilization of artificial intelligence, these systems can even compose an online attendance register of students present during the lectures. Data is primarily recorded on the hard disk of the NVR (Network Video Recorder), and in the long term, it is recommended to save the data in the blockchain. The purpose of the research is to demonstrate how university security cameras can be securely connected to the blockchain. This would be important for universities as this is sensitive student data that needs to be protected from unauthorized access. In my research, as part of the practical implementation, I therefore also use encryption methods and data fragmentation, which are saved at the nodes of the blockchain. Thus, even a DDoS (Distributed Denial of Service) type attack may be easily repelled, as data is not concentrated on a single, central server. To further increase security, it is useful to constitute a blockchain capable of its own data storage at the faculty itself, rather than renting data storage space, so we, ourselves may regulate the conditions of operation, and the policy of data protection. As a practical part of my research, therefore, I created a blockchain called UEDSC (Universities Data Storage Chain) where I saved the student's data.

关键词： Blockchain Technology Security Camera Data Security Artificial intelligence

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A motion compression method by fuzzy relational equations

A motion compression method by fuzzy relational equations

引用

IEEE international symposium on computational intelligence in robotics and automation

作者： Nobuhara, H Hirota, K Tokyo Inst Technol Dept Computat Intelligence & Syst Sci Tokyo 152 Japan

ISBN: (纸本)0780378660

A motion compression method by max t-norm composite fuzzy relational equations (MCF) is proposed. In the case of MCF, a motion sequence is divided into intra,pictures (I-pictures) and predictive-pictures (P-pictures). The I-pictures and the P-pictures are compressed by using uniform coders and non-uniform coders, respectively. In order to perform an effective compression and reconstruction of the P-pictures, a design method of non-uniform coders is proposed. The proposed design method is based on an overlap level of fuzzy sets and a fuzzy equalization. Through an experiment using 10 P-pictures, it is confirmed that the root means square errors of the proposed method is decreased to 89.4% of the uniform coders, under the condition that the compression rate is 0.0057. A result of motion compression and reconstruction of motion (standard motion imagery) by MCF is also presented.

关键词： Design

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Multi-objective Evolutionary Algorithm Based Graph Neural Network Architecture Search

Multi-objective Evolutionary Algorithm Based Graph Neural Ne...

引用

11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： He, Lianyi Liu, Xiaobo Xiang, Hongbo Wang, Guangjun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences Wuhan430074 China

ISBN: (纸本)9789819647521

Graph Neural Networks (GNN) has become a powerful graph data processing method, which has been widely used in node classification, link prediction, and other graph analysis tasks. Due to the diversity and complexity of graph structures and information propagation, as well as the handling of heterogeneous graphs, etc., the design of GNNs presents many challenges. The existing methods have high classification accuracy, but their structures are very complex. In this paper, a graph neural network architecture search framework named MO-GNN, which is based on multi-objective evolutionary algorithm is proposed. Furthermore, a weight sharing strategy MO-GNN-WS is proposed to reduce the resource consumption caused by weight training of different architectures. To verify the performance of the proposed algorithm, experiments on four popular graph datasets are used for transduction and induction tasks. The experimental results show that the MO-GNN-WS algorithm outperforms the most advanced neural network architecture search methods in terms of classification accuracy and resource consumption. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data Sharing

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Systematic design of switched reluctance motor drive based on the intelligent computational software package

Systematic design of switched reluctance motor drive based o...

引用

IEEE international symposium on computational intelligence in robotics and automation

作者： Chen, H Meng, X Zhang, D China Univ Min & Technol Dept Automat Xuzhou 221008 Peoples R China

ISBN: (纸本)0780372034

The principles for the design of the Switched Reluctance motor drive based on the intelligent computational software package are presented by taking a three-phase 12/8 structure Switched Reluctance motor drive for the joint of the robot for example. The design could be done from the systematic point of view, considered the motor, the power converter and the control strategy as a whole. The Output equation relating to the relationship between the structure parameters and the electric loads is derived. The equation of the turn numbers of the phase winding is also advanced. The design procedure is given. Some interfaces of the intelligent computational software package at the condition of Windows 9X in English are given. The design is checked by the prototype. The accuracy is checked by the experimental measurement of the developed prototype. It is shown that the design has the advantages in practicality and high precision.

关键词： Electric drives

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Research of Sequential Recommendation Algorithm Based on Contrastive Learning and Causal Learning

Research of Sequential Recommendation Algorithm Based on Con...

引用

11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： Wang, Tong Dai, Yaping Shao, Shuai School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819647521

In sequential recommender systems, two primary challenges are the long-tailed distribution of data and data distribution bias. To effectively address these issues, a Contrastive and Causal Learning Algorithm for Sequential Recommendation (C2ASeRec) has been proposed. The algorithm enhances the training efficacy of sequential recommendation models and boosts their performance by introducing environment partition and reweighting, regularization term constraint based on causal learning, and methods to enhance uniformity of representation. These innovations mitigate the performance degradation previously caused by data distribution bias. By concurrently incorporating causal learning-based regularization constraints and representation uniformity enhancement techniques, C2ASeRec demonstrates both universality and robustness across different environment partitioning principles, enabling superior performance in complex real-world scenarios. Experimental results indicate that C2ASeRec achieves outstanding outcomes in addressing data distribution bias. In terms of key performance metrics such as hit rate and normalized discounted cumulative gain, our algorithm significantly surpasses seven previous methods, showcasing exceptional advanced performance. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Graph Attention Convolutional Neural Network Combined with Transformer Classification Method for Small Sample Datasets

Graph Attention Convolutional Neural Network Combined with T...

引用

11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： Lei, Rongzhen Yang, Fan Ren, Yanhui School of Instrument Science and Opto-Electronics Engineering Beijing Information Science and Technology University Beijing100192 China Department of Automation Tsinghua University Beijing10084 China

ISBN: (纸本)9789819647521

In view of the shortcomings of deep learning methods in modeling small sample fault data, this paper proposes a fault classification method based on Graph Attention Convolutional Neural Network (GATCN) combined with Transformer, which can be well adapted to small sample fault data sets. Firstly, the multi-dimensional sensor data is converted into a multi-component graph representation, and the weights of the edges are updated by the attention mechanism between the nodes of the graph to represent the topological structure between different nodes, to extract the correlation between the multi-component parameters. Then, the Transformer module learn the extracted spatial features to capture the temporal feature relationships of the time series data. Finally, the classification layer based on Softmax is used to classify faults. The model is demonstrated on the TEP data set and the fault datasets from three satellite subsystems. The results show that our model is superior for small sample fault data sets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Integrating computer vision libraries in networked robotic systems

Integrating computer vision libraries in networked robotic s...

引用

2005 IEEE international symposium on computational intelligence in robotics and automation CIRA 2005

作者： Cervera, Enric Laboratory of Robotic Intelligence Jaume-1 University Campus Riu Sec 12071 Castelló Spain

The niche where computer vision software meets networked robotics remains unfilled so far. Descending costs, and technological advances in wireless communications, digital video capture, and computing power provides roboticists with powerful yet affordable tools to develop cooperative, distributed, vision-based control tasks. This paper presents a consistent framework for such networked, visually-controlled environments, where the main assumption is that video may be captured, processed, and used for control in different machines across the network. To do so, care has been taken in order to ensure efficiency, scalability, and reusability of software. The presented framework aims to seamlessly integrate rock-solid, fast, existing vision processing libraries within a cross-platform, distributed environment, based on Java and agents. Different applications in real setups are envisioned. © 2005 IEEE.

关键词： robotics

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