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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4197 条记录，以下是51-60 订阅

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Integrated optimization based on HSV color mode and frequency domain processing 7

Integrated optimization based on HSV color mode and frequenc...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Li, Tao Ningxia University Xixia District Ningxia Hui Autonomous Region Yinchuan City China

ISBN: (纸本)9798350375107

In this paper, we propose an ophthalmic image processing algorithm that integrates the use of HSV color mode, Fourier transform, Butterworth filter and histogram equalization, aiming to improve the quality of ophthalmic images and enhance the vascular structure and details, so as to improve the diagnostic accuracy and reliability of doctors' diagnosis of ophthalmic diseases. First, by converting the original image to HSV color mode, we are able to separate the luminance channel of the image so that the luminance information of the image can be processed more efficiently without affecting its color and details. Next, a Fourier transform is performed on the luminance channel signals to convert the image from the spatial domain to the frequency domain in order to better understand the frequency characteristics and texture information of the image. then, a Butterworth filter is applied to the V channel in the frequency domain to separate the high and low frequency signals of the image in order to highlight the vessel structure and details. On this basis, the high-frequency signal is superimposed on the original luminance signal, and the local contrast of the image is enhanced by Fourier inverse transform and histogram equalization to make the blood vessel structure more visible. Finally, the processed V-channel signal replaces the V-channel signal of the original image to output the enhanced image. With this algorithm, the enhancement of texture and structure of ophthalmic images is effectively realized, avoiding the loss of information due to overexposure and distortion, and providing ophthalmologists with a more accurate and reliable diagnostic tool. © 2024 IEEE.

关键词： Butterworth filters

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Adversarial Attack and Defense on Machinery Fault Diagnosis 7

Adversarial Attack and Defense on Machinery Fault Diagnosis

引用

7th IEEE international conference on information Systems and computer Aided Education, ICISCAE 2024

作者： Jia, Jiazhen Fu, Songyin Yan, Diqun College of Information Science and Engineering Ningbo University Ningbo China Information Center Ningbo University Ningbo China

ISBN: (纸本)9798350350760

In the field of mechanical fault diagnosis, deep learning models have demonstrated strong performance. However, limited focus has been directed towards the robustness of these models in resisting adversarial attacks. In this research, we concentrate on adversarial attacks aimed at deep learning-based machinery fault diagnosis systems, investigating both untargeted and targeted conditions. Experimental results reveal a significant reduction in the performances of typical deep learning-based models following adversarial attacks. Additionally, an effective defense scheme employing data normalization is proposed to protect victim models. this study provides a pioneering examination of adversarial examples in machinery vibration signals, contributing to the development of protection methods against adversarial attacks and the enhancement of deep learning-based model robustness. ©2024 IEEE.

关键词： Adversarial machine learning

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Bluffing the Hackers: Automated Decoy Creation and Real-Time Cyber Deception 7

Bluffing the Hackers: Automated Decoy Creation and Real-Time...

引用

7th international conference on Signal processing and information Security, ICSPIS 2024

作者： Farrag, Mohamed Sayed, Samir G. Zamzam, Marwa German International University Faculty of Informatics and Computer Science Cairo Egypt Giza Egypt Helwan University Faculty of Engineering in Helwan Cairo Egypt

ISBN: (纸本)9798350368673

In the digital age, the proliferation of cyber threats necessitates advanced cybersecurity solutions. this paper introduces 'Bluff,' an innovative cybersecurity platform designed to enhance intrusion prevention through automated decoy deployment and real-time threat tracking. 'Bluff' integrates both backend and frontend components within a single cross-platform executable, simplifying installation and use. Leveraging deception technology, 'Bluff' creates strategic decoys that divert cyber attackers, thereby protecting critical systems and gathering valuable threat intelligence. this comprehensive solution not only fortifies defenses but also manipulates adversaries' perceptions, enabling early threat detection. through detailed implementation and performance evaluation, we demonstrate 'Bluff's' efficacy in providing a proactive and sophisticated defense mechanism, contributing significantly to the evolving landscape of cybersecurity. © 2024 IEEE.

关键词： Cyber attacks

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Research on Plant Leaf Disease Identification Based on a Long-Distance Feature Fusion Model 7

Research on Plant Leaf Disease Identification Based on a Lon...

引用

7th international conference on computer information Science and Application technology, CISAT 2024

作者： Wang, Junxia Hu, Tingting Yang, Shengying Hua, Haotian Zhang, Shuping Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou310023 China Xinjiang Institute of Technology Aksu735400 China

ISBN: (纸本)9798350375107

Plant diseases cause significant global crop losses, making early detection crucial. Traditional deep learning models often neglect global context, reducing accuracy. To address this, we propose a ResNet50-based model with a long-distance feature enhancement module to capture global dependencies and focus on disease texture features. We also use disease patch augmentation to expand the dataset and address sample diversity issues. Transfer learning with pre-trained models boosts early stage performance. Our model achieves 99.58% accuracy on the PlantVillage dataset, outperforming DenseNet, ResNet50, MobileNet, and Inception V3 by 0.58%-4.56%, significantly enhancing plant disease identification accuracy. © 2024 IEEE.

关键词： Plant diseases

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Near-field Source DOA Estimation Algorithm Based on De-impact Function under Impulse Noise 7

Near-field Source DOA Estimation Algorithm Based on De-impac...

引用

7th IEEE international conference on Electronic information and Communication technology, ICEICT 2024

作者： Xu, Xingchao Pang, Baohe Li, Yingsong Li, Liping Zou, Dingcheng Zlatanov, Nikola Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China Innopolis University Faculty of Computer and Engineering Sciences Innopolis Russia

ISBN: (纸本)9798350384437

In addressing the issue of localizing near-field source signals in the presence of impulse noise, this manuscript introduces a novel de-impact function designed for preprocessing received signals to alleviate the interference caused by impulse noise. Simulation experiments verify the effectiveness of the proposed de-impact function in effectively suppressing impulse noise. Furthermore, to augment estimation precision, a novel algorithm for near-field source localization is proposed. Building upon the framework of correlation entropy theory, a new correntropy covariance matrix is formulated to replace the original signal covariance matrix for signal processing. through a succession of low-bias approximations between near-field and far-field scenarios, the algorithm converts the original 2-D search into 1-D operations. Additionally, the conventional spectral peak search is replaced by polynomial solving to further mitigate the computational complexity of the algorithm. © 2024 IEEE.

关键词： Impulse noise

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Design of Intelligent Teaching Evaluation System Based on Emotion Recognition Algorithm 7

Design of Intelligent Teaching Evaluation System Based on Em...

引用

7th international conference on Education, Network and information technology, ICENIT 2024

作者： Xue, Wei Liu, Jie Guangxi Vocational Normal University School of Communications Nanning China Guangxi Vocational Normal University School of Computer and Information Engineering Nanning China

ISBN: (纸本)9798350374919

Recently, with the rapid development of artificial intelligence technology, emotion recognition algorithms provide new possibilities for innovative intelligent teaching evaluation methods, which is both an important direction for the development of modern educational technology and a research hotspot in the field of educational evaluation. Taking the emotion algorithm as the theoretical basis and using advanced computer vision technology, this paper designed an intelligent teaching evaluation system based on facial expressions and postural movements to accurately assess the classroom status of students in real time. the system uses residual network model to classify and recognize facial expressions and postural movements, and designs an event statistical model to calculate student engagement and status scores as one of the reference indicators for quality evaluation in real-time classrooms. the experimental results show that the system can correctly record the real-time situation of the classroom, provide educators with intelligent teaching evaluation, innovate the teaching evaluation system, and provide a strong guarantee for improving the quality of teaching and the learning effect of students. © 2024 IEEE.

关键词： Emotion Recognition

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A Wideband Circularly Polarized Folded Transmitarray Antenna With Linearly Polarized Feed 7

A Wideband Circularly Polarized Folded Transmitarray Antenna...

引用

7th IEEE international conference on Electronic information and Communication technology, ICEICT 2024

作者： Sun, Xiangdong Guo, Xulong Li, Yin Zhang, Yongliang Li, Yingsong Inner Mongolia University School of Electronic Information Engineering Hohhot010021 China Inner Mongolia University Inner Mongolia Branch of National Computer Network Emergency Response Technical Team Coordination Center of China Hohhot010020 China Peng Cheng Laboratory Shenzhen518000 China Inner Mongolia University School of Transportation Institute Hohhot010021 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing China

ISBN: (纸本)9798350384437

A low-profile, high-gain, wideband circularly polarized folded transmitarray antenna (CPFTA) is proposed, and a polarization-selective linear-to-circular polarization (LP-CP) conversion element is introduced. the CPFTA consists of a linearly polarized (LP) magnetoelectric dipole antenna and a circularly polarized (CP) helical patch antenna. the CPFTA demonstrates excellent performance with a 3dB gain bandwidth of 29.5% and a 3dB axial ratio (AR) bandwidth of 40.9%. © 2024 IEEE.

关键词： Circular polarization

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GRU-Based Winner Subcarrier Detection in Frequency Domain Contention 24

GRU-Based Winner Subcarrier Detection in Frequency Domain Co...

引用

7th international conference on information Science and Systems, ICISS 2024

作者： Yao, Shumin Zhao, Qinglin Xu, Zezhou Feng, Li Li, Guanghui Tian, Liwei Sun, Yi School of Computer Science and Engineering Macau University of Science and Technology China Department of Broadband Communication Pengcheng Laboratory China School of Artificial Intelligence and Computer Science Jiangnan University China Department of Computer Guangdong University of Science and Technology China Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9798400717567

Single-carrier frequency domain contention (S-FDC) is an efficient wireless contention mechanism based on orthogonal frequency-division multiplexing (OFDM). In each round of S-FDC, each node randomly selects and signals on one of the OFDM subcarriers while listening to all subcarriers simultaneously. Each node independently detects the activated subcarrier with the smallest index and regards it as the winner subcarrier. Accurately detecting the winner subcarrier is crucial to ensuring the functionality of the network. However, it is extremely difficult in practice due to power leakage problems that arise from frequency asynchronization among nodes. In this paper, we propose a gated-recurrent-unit (GRU)-based model that incorporates S-FDC’s unique features as domain knowledge to enable accurate winner subcarrier detection. Extensive simulation experiments verify that our DL model is effective and outperforms state of the art. this research highlights the potential of DL in improving wireless communication systems. © 2024 Copyright held by the owner/author(s).

关键词： Frequency domain analysis

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Research on Visual Malicious Code Classification Based on Improved Faster R-CNN 7

Research on Visual Malicious Code Classification Based on Im...

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7th international conference on computer and information processing technology, iscipt 2022

作者： Zhen, Liang Zhao, Yuntao Shenyang Ligong University College of Information Science and Engineering Liaoning Shenyang110159 China

With the development of Internet technology, the number of malicious software is increasing and malicious attacks are becoming rampant. therefore, the research on malicious software has a great application prospect. this paper proposes a visual malicious code classification method based on improved Faster R-CNN. Rank & Sort Loss is used to optimize the loss function of the Faster R-CNN model, in order to reduce the number of hyperparameters, improve the performance of the model, and make it more robust to the problem of class imbalance in training. the experimental results show that using the improved Faster R-CNN detection method has a further improvement in the recognition accuracy of malicious code grayscale images compared with the classic Faster R-CNN detection method. © 2022 Copyright for this paper by its authors.

关键词： Object detection

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Research on Building a Standardized Library for Auditing Heterogeneous information Models in Distributed Data 7

Research on Building a Standardized Library for Auditing Het...

引用

7th IEEE international conference on information Systems and computer Aided Education, ICISCAE 2024

作者： Heping, Huang Zhonglu, Zou Zhicai, Huang Dongguan Power Supply Bureau Guangdong Power Grid Corporation Guangdong Dongguan523000 China

ISBN: (纸本)9798350350760

With the advancement of smart grid transformation, the configuration audit of distribution network communication networks faces challenges such as diversified network devices, numerous manufacturers, and multi-source data management. Traditional methods exhibit significant deficiencies in processing efficiency and data consistency, failing to meet the demands of large-scale data management. this paper proposes a standard library construction method for configuration audit of distribution network data networks. By integrating knowledge graph technology with convolutional neural networks, this method establishes dynamic and static audit libraries, achieving accurate, rapid, and comprehensive management of audit data. the specific process includes the collection and preprocessing of multi-source data, construction of the knowledge graph, application of the inference mechanism, and intelligent retrieval and updating of the standard library. this method significantly improves the accuracy and completeness of data security configuration and optimizes the configuration audit process of distribution network communication networks. ©2024 IEEE.

关键词： Data consistency

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