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检索条件"任意字段=2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023"

共 3023 条记录，以下是341-350 订阅

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Privacy-preserving data Splitting Based on Machine Learning 3

Privacy-preserving Data Splitting Based on Machine Learning

引用

3rd international conference on Electronic Information Engineering and computer, EIECT 2023

作者： Ruan, Huafeng Dongguan University of Technology School of Computer Science and Technology School of Software School of Cyberspace Security Dongguan China

ISBN: (纸本)9798350357707

Privacy-preserving data splitting is an effective means of storing parts of data across different servers to safeguard user privacy. Current privacy protection schemes that employ data splitting for privacy protection assume that data owners are already aware of the constraints between attributes, which limits their applicability. To address this challenge, we propose a scheme that utilizes machine learning to segment anonymous data and securely store it. Initially, we employ machine learning algorithms to recursively compute the relationships between attributes. Subsequently, we introduce a greedy algorithm that leverages the relationships derived in the previous step to calculate a data fragmentation approach that ensures privacy safety. Experimental results indicate that our scheme can successfully derive privacy-safe fragmentation methods using various machine learning algorithms. Among the four machine learning algorithms tested, Lasso regression demonstrated the fastest computation speed. © 2023 ieee.

关键词： Privacy-preserving techniques

来源：评论

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Decentralized Operator Screening Scheme for Near-data Processing Models Based on Precedence Relationships 3

Decentralized Operator Screening Scheme for Near-Data Proces...

引用

3rd international conference on Electronics and Information Technology, EIT 2024

作者： Huang, Pengteng He, Yantao Chen, Guanyu Nie, Jun Guangdong University of Science and Technology Department of Computer Science Guangdong Dongguan China

ISBN: (纸本)9798350369151

This paper addresses the issue of data transmission bottlenecks in traditional database management systems when handling large-scale data. It proposes a filtering scheme for operators under the near-data processing model, based on precedence relations. This scheme conducts an in-depth analysis of the precedence relations in the execution sequence of database operators to identify which ones are more suitable for delegation to intelligent storage devices, thereby reducing unnecessary data migration. The research indicates that this strategy can effectively prevent reverse data transmission and significantly reduce the volume of data transmitted on the bus. This results in a substantial improvement in system processing efficiency and a reduction in energy consumption. Experimental verification demonstrates that the filtering scheme based on precedence relations is significantly superior to the traditional filtering method that relies solely on the ratio of input/output data volume. This provides strong support for the development of more efficient database management systems. © 2024 ieee.

关键词： data transfer

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TFC-net: Transfer Fusion-Compression Learning Network for Few-Shot Surface Defect Detection 3

TFC-net: Transfer Fusion-Compression Learning Network for Fe...

引用

3rd international conference on computer science, Electronic Information Engineering and Intelligent Control Technology, CEI 2023

作者： Rao, Zeyuan Zhang, Zhe Zhao, Ruixiang Lv, Wu Ma, Jie China-EU Institute for Clean and Renewable Energy Huazhong University of Science and Technology Wuhan China Huazhong University of Science and Technology Wuhan China Cssc Navigation Technology Co. Ltd Beijing China

ISBN: (纸本)9798350372052

Defect detection is a prevailing application within industry, while the scarcity of defect sample set a challenge for general deep learning method which requires enormous data for training. Considering the problem of few-shot learning in surface defect detection, inspired by transfer learning, we propose a two-stage TFC-net (Transfer Fusion and Compression few-shot learning network). For Transfer Fusion (TF) module, we fuse three networks pretrained on large scale dataset as prior knowledge to extract feature of defect samples and unify the feature distribution. For Transfer Compression (TC) module, we gradually mining representative feature of distinct defects to make classification. Experiments carried on three surface defect datasets extensively show our method achieves superior performance compared with competing methods, while the transfer speed consistent with metric learning which requires no training. © 2023 ieee.

关键词： Surface defects

来源：评论

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Power data Operation Effectiveness Analysis Based on Multi-dimensional Analysis 3

Power Data Operation Effectiveness Analysis Based on Multi-d...

引用

3rd international conference on Consumer Electronics and computer Engineering, ICCECE 2023

作者： Deng, Zhidong Li, Yanyan Xing, Wei Zhang, Mingjie Gong, Jian State Grid Customer Service Center Tianjin300300 China

ISBN: (纸本)9798350331578

To reduce the absolute error of the effectiveness of power data operation analysis, build a more stable and multivariate analysis structure, and maximize the reliability of the overall analysis results, a new power data operation effectiveness analysis method based on multi-dimensional analysis is designed. Set up nodes and collect data. Design equivalent analysis links according to the amount of data, adopt the multi-dimensional analysis method, construct multi-dimensional data operation effectiveness analysis sovereignty model, and combine with directional processing mechanism to realize the power data operation effectiveness analysis. The test results show that compared with the traditional multi-mechanism data operation effectiveness analysis test group and the traditional data sovereignty operation effectiveness analysis test group, the absolute error of the effectiveness analysis of the multi-dimension analysis method is smaller, and the error value is only 1. This analysis method is more reliable and accurate in dealing with data operation and has practical application value. © 2023 ieee.

关键词： Multivariant analysis

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Dynamic 1X/2X CMOS Rectifier for 5G-IoT Wireless Power Transfer applications 3

Dynamic 1X/2X CMOS Rectifier for 5G-IoT Wireless Power Trans...

引用

3rd ieee international conference on Electronic Communications, Internet of Things and Big data, ICEIB 2023

作者： Wang, Tao National Chung-Shan Institute of Science and Technology Taoyuan Taiwan

ISBN: (纸本)9798350333862

An auto-tuned dynamic CMOS rectifier is proposed to supply VDD relief, cover an input range of 3-5V, and reduce the burden of the following stage. The rectifier is pulse-width modulator (PMW) free, too. Conventional duty-cycle control is significantly simplified by using a full bridge and inverter buffers. VDD-free comparators and dynamic body biasing techniques are also adopted to relieve the constraint coming from VDD. Compared to the circuit implementations on similar semiconductor processes, the proposed rectifier showed a power efficiency of 78 to 90% and significantly expanded application flexibility to support various input power levels for IoT platforms. © 2023 ieee.

关键词： Internet of things

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Brightness Attention Mechanism for Few-Shot Action Recognition 3

Brightness Attention Mechanism for Few-Shot Action Recogniti...

引用

3rd international conference on Electronic Information Engineering and computer science, EIECS 2023

作者： Tian, Zhiyuan Xue, Wanli Zhang, Ying Tianjin University of Technology School of Computer Science and Engineering Tianjin300384 China

ISBN: (纸本)9798350316674

Few-shot action recognition remains a challenging problem in computer vision, particularly in scenarios where the model needs to generalize well from limited examples. In this study, we present a novel concept known as the Brightness Attention Mechanism(BAM), seamlessly integrated into the ResNet50 architecture, to enhance the model's sensitivity to brighter regions in the image. Our approach begins with the use of an image segmentation model that isolates human figures, followed by blending these segmented images with original images to accentuate the subject. We then apply BAM to give more attention to these highlighted regions during the action recognition task. The data from our experiments reveal a marked increase in the accuracy of few-shot action recognition, surpassing both conventional techniques and the latest attention-based methods. Our methodology advances the state of the art for few-shot scenarios across Kinetics, HMDB51, and UCF101. © 2023 ieee.

关键词： action recognition brightness attention computer vision image fusion

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Research on Intelligent System of 3D Software Cultural and Creative Product Design Based on computer Artificial Intelligence Technology

Research on Intelligent System of 3D Software Cultural and C...

引用

data science and computer application (icdsca), ieee international conference on

作者： Yuan Xing College of Fine Arts and Design Xi'an University Xi’an China

This paper proposes a development scheme of 3D animation visual mobile application based on virtual reality technology. Use camera equipment to collect image data. The image-real technology is used to process the images and other contents that need to be made. The processed data is established, combined with sound effects and other technologies, and input into the Unity3D engine to generate a 3D virtual picture at last. Establish a database of cultural and creative pictures. Quantitative description of the artistic style of cultural and creative products is carried out, and artificial features such as composition and splicing edge features are extracted. The advanced semantic properties are studied by simulated annealing method. Research the stitching method of artistic cultural and creative commodity pictures. Simulation experiments show that the proposed method can effectively complete the intelligent design of three-dimensional creative products.

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Early Screening Prediction System of Breast Cancer MRI Images Based on Deep Learning 3

Early Screening Prediction System of Breast Cancer MRI Image...

引用

3rd ieee international conference on Electrical Engineering, Big data and Algorithms, EEBDA 2024

作者： Xu, Li Liu, Liang Baotou Medical College Inner Mongolia University of Science and Technology Department of Computer Science and Technology Baotou014040 China

ISBN: (纸本)9798350380989

With the increasing incidence rate of breast cancer in China, how to effectively improve the accuracy and sensitivity of breast cancer diagnosis has become an important issue facing the Chinese medical industry. In recent years, the application of computer deep learning technology in medical images has become increasingly widespread. It can automatically extract features from images and classify and predict them. At present, deep learning has made significant breakthroughs in the field of medical image analysis. Deep learning algorithms can automatically discover disease features in massive image data, and their performance has also been significantly improved. The purpose of this study was to study and analyze breast cancer MRI (Magnetic Resonance Imaging) images by using deep learning algorithm, hoping to provide help for early diagnosis of breast cancer. The results showed that the accuracy of the early screening prediction system for breast cancer MRI images based on deep learning reached 95.6%, which laid the foundation for the early diagnosis and treatment of breast cancer. © 2024 ieee.

关键词： Breast Cancer Prediction Deep Learning Early Screening Prediction System Magnetic Resonance Imaging

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Research on Mid-Platform Scenario Operation and Maintenance System of computer Cloud Platform Based on Enhanced Risk Prevention

Research on Mid-Platform Scenario Operation and Maintenance ...

引用

data science and computer application (icdsca), ieee international conference on

作者： Zhang Helin Zheng Zhiwei Lin Dewei Chen Rui Lei Qinghai Information and Communication Branch of State Grid Fujian Electric Power Co. Ltd Fuzhou Fujian China State Grid Info-Telecom Great Power Science And Technology Co. Ltd. Fuzhou Fujian

It adopts micro-service architecture to create a safe, efficient and agile intelligent operation and maintenance integrated service platform. The system has the functions of low voltage topology recognition, intelligent anomaly research, accurate automatic order sending, auxiliary power grid planning and so on. Combined with some classical theories of situational awareness model, a situational awareness algorithm model based on improved fuzzy clustering algorithm is established. The overall operation and maintenance service platform builds the operation and maintenance service system based on the cloud computing and middle-desk architecture to realize the unified standardization and integration of the whole-domain management resource data. A trial of the system in a power company showed a 0.3% drop in the error rate.

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Emotion Recognition Based on Microstates: A Comparison between Scalp and Source Analysis 3

Emotion Recognition Based on Microstates: A Comparison betwe...

引用

3rd international conference on Electronic Information Engineering and computer science, EIECS 2023

作者： Ruan, Jie Xiao, Di Anhui University School of Computer Science and Technology Hefei230601 China

ISBN: (纸本)9798350316674

The microstate of the electroencephalogram (EEG) captures spatiotemporal information from all channels, encompassing extensive electrophysiological data. Its significance to emotion recognition is substantial. However, current research into emotion recognition based on microstates remains confined to the scalp level, and due to the effects of volume conduction, the accuracy of emotion recognition might not be optimal. In this study, we employed the sLORETA method to map scalp data onto the cortex. Subsequently, we applied spatiotemporal analysis using microstate analysis techniques and extracted various features, including duration, occurrence frequency, coverage, and transition probability. We performed classification of discrete emotional labels separately for scalp and source data within the SEED and SEED-IV datasets. For the SEED dataset, the use of K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) classifiers on source data resulted in an average classification accuracy increase of 6.07% and 5.93%, respectively, compared to the scalp. Similarly, for the SEED-IV dataset, corresponding increments of 6.85% and 7.5% were observed. These findings emphasize the efficacy of source microstate analysis in enhancing emotion recognition accuracy. © 2023 ieee.

关键词： EEG emotion recognition microstates

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