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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 10988 条记录，以下是221-230 订阅

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Facial Expression Recognition with Squeeze-and-Excitation Network 7

Facial Expression Recognition with Squeeze-and-Excitation Ne...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Guo, Peiyuan Song, Chen Beijing University of Posts and Telecommunications School of Computing Beijing China Southwest University of Science and Technology School of Computer Science and Technology Mianyang China

ISBN: (纸本)9781665478571

In this paper, we aim to propose a facial expression recognition algorithm by utilizing the spatial attention mechanism. We adopt 3 basic CNN models, including AlexNet, VGGNet and ResNet for comparison. then we add the attention module, i.e., SENet to VGGNet and ResNet for futher feature enhancement. Our results on FER2013 show the effectiveness of our method. Our VGG+SENet achieves 65.0% accuracy and our ResNet+SENet achieves 66.8% accuracy. Both method with attention can get an obvious performance promotion, which validates the effectiveness of attention mechanism. © 2022 IEEE.

关键词： Computer vision

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Video Reversible Data Hiding Based on Motion Vector 7

Video Reversible Data Hiding Based on Motion Vector

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Ning, Zhiqiang Niu, Ke Lin, Yangping Pan, Feng Engineering University of Pap College of Cryptography Engineering Xi'an China

ISBN: (纸本)9781665478571

Aiming at the problem that the existing motion vector data hiding algorithms based on two-dimensional histogram modification do not fully utilize the embedding space, a large-capacity video reversible data hiding algorithm is proposed. Firstly, the prediction error is calculated by using the prediction algorithm based on the spatial location of the motion vector, and the prediction error pair is obtained. then, the secret information is embedded by the designed embedding strategy combining two-dimensional and one-dimensional histograms. Finally, the idea of two-layer embedding is combined to further increase the embedding capacity. Compared with the latest data hiding algorithms of the same type, the embedding capacity of this algorithm is increased by an average of 2.23 times. © 2022 IEEE.

关键词： Steganography

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Cooperative Relationship Prediction between Scholars in Heterogeneous Academic Network 23

Cooperative Relationship Prediction between Scholars in Hete...

引用

23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Shi, Jia Jin, Hai Xie, Xia National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and Technology Services Computing Technology and System Lab Cluster and Grid Computing Lab Wuhan China School of Computer Science and Technology Hainan University Haikou China

ISBN: (纸本)9781665494571

the real academic network belongs to a heterogeneous network, therefore, for the link prediction tasks, some information on the network may be lost if only using homogeneous network methods. In order to make good use of the rich semantic information in a heterogeneous network for better predicting the cooperative relationship between scholars, this paper proposes a cooperative relationship prediction (CoRP) model. the CoRP model includes the following three steps. Firstly, a structural feature extraction module is designed based on meta path by using the similarity metric function to measure the meta path similarity between scholars. Secondly, to overcome the defects that the existing methods usually ignore the attribute information on nodes, three attribute feature presentation functions are constructed to fully utilize the attribute information of scholars in the academic network. In the end, a machine learning classifier which combines the structural similarity and attribute similarity is utilized to learn each attribute feature and complete the task of cooperative relationship prediction. the experimental results reveal that compared with the benchmark method, the proposed method has better performance and interpretability with improvement from 3% to 10% of AUC value for the AMiner academic data set. © 2021 IEEE.

关键词： Measurement Smart cities Semantics Machine learning Benchmark testing Predictive models Feature extraction

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Multipath Congestion Control in Integrated Intelligent Network 7

Multipath Congestion Control in Integrated Intelligent Netwo...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Li, Yinglin Yang, Li Qi, Yaowen Wei, Debin Dalian University Dept. College of Information Engineering Dalian China Nanjing University of Science and Technology Dept. School of Automation Nanjing China

ISBN: (纸本)9781665478571

In the integrated intelligent network, the high dynamics and high loss of satellite network leads to low bandwidth utilization. Furthermore, due to various necessary in satellite network, it is hard to meet the quality of service (QoS) requirement. In the present paper, we propose a novel congestion control algorithm (CCA) based on bottleneck bandwidth and round-trip time estimation for multipath TCP over the integrated intelligent network, which called AMPTCP-RB. In this work, we continuously estimated round-trip propagation time by calculating the link length and estimating bottleneck bandwidth by ack rate and send rate to evaluation congestion state, and then determined the decrease factor through utility function based on various QoS requirement. the result shows that proposed CCA enhances the total throughput performance and guaranteed the QoS. © 2022 IEEE.

关键词： Quality of service

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Performance Analysis of Turbo Codes for 5G Massive Machine-Type Communication(mMTC) 23

Performance Analysis of Turbo Codes for 5G Massive Machine-T...

引用

作者： Adamu, Mohammed Jajere Qiang, Li Zakariyya, Rabiu Sale Jabire, Adamu Halilu Kawuwa, Halima Bello Saminu, Sani Tianjin University School of Microelectronics Tianjin China Department of Electronics Science and Technology Hefei China Taraba State Umiversity Department of Electrical and Electronics Taraba Nigeria School of Precision Instrument and Opto-electronics Engineering Tianjin University Tianjin China University of Ilorin Department of Biomedical Engineering Ilorin Nigeria

ISBN: (纸本)9781665494571

In our present and future wireless communication systems, high-performance codes with low design complexity are required for optimum coding gain. In this paper, an efficient Long Term Evolution (LTE) based Turbo decoding algorithm is proposed. it is derived by remodeling the conventional maximum a posteriori probability (MAP) decoder. the proposed scheme aims to reduce the complexity of actualizing the conventional MAP Turbo decoder in the newly mMTC PHY layer features. the overall system performance is analyzed in terms of bit error rate (BER). © 2021 IEEE.

关键词： Maximum a posteriori estimation Wireless communication Analytical models System performance Bit error rate Turbo codes Mathematical models

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FWIB: Fuzzy Weighted Iterative Bayes Algorithm 7

FWIB: Fuzzy Weighted Iterative Bayes Algorithm

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Wang, Tianhan Zhang, Weidong Lin, Dayong Beijing Institute of Technology School of Information and Electronics Beijing China Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab Beijing China

ISBN: (纸本)9781665478571

Within the theoretical framework of Naive Bayes(NB), Iterative Bayes(IB), as an important variant, was proposed to alleviate the attribute interdependence problem based on output adjustment technique and shows certain performance enhancement. However, like NB, IB also suffers from biased classification and poor robustness against noise on class imbalanced data. To address these problems, cost-sensitive learning is introduced, and by assigning fuzzy-membership values to training data, we propose a class of Fuzzy Weighted Iterative Bayes algorithms (FWIB-CE, FWIB-HE, FWIB-CL-HL) to integrate more prior information from the sample distribution. the experimental results on ten typical imbalanced datasets show our methods have significant outperformance over NB and IB under G-mean evaluation in classification and have higher robustness against noise interference. © 2022 IEEE.

关键词： Classification (of information)

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Research on Overlapping Community Detection Based on Density Peak Clustering in Heterogeneous Networks 7

Research on Overlapping Community Detection Based on Density...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Yue, Sun Yuhong, Zhao Inner Mongolia University of Science and Technology School of Information Engineering Baotou China

ISBN: (纸本)9781665478571

To solve the problem of finding overlapping communities in heterogeneous networks, this paper proposes a model for finding overlapping communities in heterogeneous networks based on density peak clustering. the model improves the heterogeneous graph attention network, which fully mines for the important information of nodes and meta-paths in information representation from the node level and the semantic level attention mechanisms and performs hierarchical aggregation to obtain heterogeneous graph embedding vectors. It combines the heterogeneous graph attention network with density peak clustering and calculates node density and relative distance through the heterogeneous graph embedding vector to divide community center nodes. then it also uses the weight information of the node-level attention mechanism to generate a community membership matrix. the experimental results on real datasets show that the model can utilize the diversity of heterogeneous network node information to discover overlapping communities with good stability and accuracy. © 2022 IEEE.

关键词： Heterogeneous networks

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Q-learning based algorithm for small-world network generation 7

Q-learning based algorithm for small-world network generatio...

引用

7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Li, Shuai Lin, Shengnan Su, Yang Engineering University of Pap College of Cryptographic Engineering Xi'an China

ISBN: (纸本)9781665478571

Small-world networks are an important type of complex network structures with small average shortest path lengths and large average clustering coefficients. A variety of generation algorithms for small-world networks have been given in existing studies, but less attention has been paid to how to optimize the small-world property of generative networks. In this paper, considering multiple objective optimization problems, small-worldness is defined to evaluate the small-world properties of generative networks, and Q-learning-based algorithms for small-world network generation are proposed and compared with WS small-world networks. Compared with the WS small-world network, the network generated by the Q-learning algorithm performs better in each metric. © 2022 IEEE.

关键词： Multiobjective optimization

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A CAN Bus anomaly Detection Based on FLXGBoost Algorithm 23

A CAN Bus anomaly Detection Based on FLXGBoost Algorithm

引用

作者： Wang, Jie Mo, Xiuliang School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781665494571

Along with the networking and automation of smart vehicles and the accelerated application of information and communication technologies, Controller Area Network (CAN) has become the most commonly used protocol in automotive bus networks, but it cannot protect the in-vehicle network from attacks because it does not provide a security system against network and physical attacks, so it is necessary to develop anomaly detection countermeasures to secure the CAN bus. this article proposes a CAN bus anomaly detection model for masquerade attacks, mining the distribution characteristics of each byte of Data messages of all IDs without the bus message identification function, combining the information entropy of message IDs to compose a new data set;introducing a focal loss function to improve the XGBoost algorithm for the case of sample imbalance, and realizing the FLXGBoost-based algorithm. the experimental results show that the anomaly detection model has a high accuracy rate in resisting tampered data domain messages. © 2021 IEEE.

关键词： Protocols Smart cities Computational modeling Memory management Feature extraction Data models Information and communication technology

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Fault Diagnosis of Rolling Bearing Using Multiscale Fusion Convolutional Neural Network 23

Fault Diagnosis of Rolling Bearing Using Multiscale Fusion C...

引用

作者： Ren, Mengyuan He, Yiming Wang, Qiang Sun, Jingtao School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China School of Mechanical Science & Engineering of Hust Huazhong University of Science and Technology Wuhan China Hitachi Ltd. Research & Development Tokyo Japan

ISBN: (纸本)9781665494571

With the automation and complexity of industry, the production planning and scheduling of the smart factory depends on the proper functioning of each part. As a key component of rotating machinery, the faults of rolling bearing is prone to effects under complex and changing working conditions and coupled with other components. therefore, it is necessary to carry out efficient and accurate fault diagnosis for rolling bearings to ensure the reliability and stability of mechanical equipment operation. this paper introduces a multi-scale rolling bearing fault diagnosis method (MSF-CNN) based on dilated convolution which is able to automatically capture complementary data and feature information of different scales of the original vibration signal through multi-scale convolution to achieve end-to-end fault diagnosis. the experimental results show that the proposed fault diagnosis method achieves an average accuracy of 99.35% under three load conditions. In addition, this method can provide the cross domain data solution to reduce the dependence on missing label data, which achieves the fault diagnosis accuracy of 89+%. It verifies the validity of our proposal. © 2021 IEEE.

关键词： Fault diagnosis Vibrations Support vector machines Convolution Smart cities Rolling bearings Feature extraction

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