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Chinese Automation Congress (CAC)

作者： Lihong Zhao Qiang Gao Xiao Yu Yu Song Tianjin University of Technology Tianjin China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

In order to diagnose the thermal anomaly of electrical equipment in time, an improved Canny edge detection algorithm for infrared image of electrical equipment is proposed to facilitate fault location. To improve the dexterity and adaptive ability of Canny edge detection algorithm, wavelet transform and improved homomorphism are used Instead of Gauss filter, the filtering algorithm can denoise the image, reduce the influence of noise and light, keep the edge intensity and details; improve Sobel operator, increase the gradient amplitude in 45 0 and 135 0 directions, so as to improve the edge positioning effect; use non maximum suppression to refine the image, and use Otsu algorithm according to the image gray level to adaptively obtain high and low thresholds, and use high and low thresholds Value algorithm detects and connects edges. Through the image verification of electrical equipment, the experimental data shows that the improved algorithm has better detection accuracy and stronger adaptability than Canny edge detection algorithm.

关键词： Image edge detection Control theory Filtering Noise reduction detection algorithms

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Accurate Onset detection Algorithm using Feature-Layer-Based Deep Learning Architecture

Accurate Onset Detection Algorithm using Feature-Layer-Based...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Ping-Hung Chen Jian-Jiun Ding Jin-Yu Huang Tzu-Yun Tseng Communication Engineering National Taiwan University Taipei Taiwan

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Onsets are criterion points to separate an audio signal into several notes. In this paper, we combine the advantages of conventional rule-based onset detection methods and convolutional neural network (CNN) based methods and propose an advanced onset detection algorithm. Different from rule-based methods, we apply the CNN to avoid tuning thresholds empirically. Different from existing CNN-based methods, which apply the original signal as the input directly, we construct a data with 204 feature layers and use it as the CNN input. Simulations show that the proposed algorithm has much better performance than both rule-based and existing CNN-based onset detection methods.

关键词： Feature extraction detection algorithms Time-frequency analysis Signal processing algorithms Signal processing Time-domain analysis Convolutional neural networks

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Three-stage Junction detection in Document Images

Three-stage Junction Detection in Document Images

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Computer Science and Software Engineering (CSASE), Conference on

作者： Hasan S.M. Al-Khaffaf Abdullah Z. Talib Department of Computer Science University of Duhok Duhok Kurdistsan Region Iraq School of Computer Sciences Universiti Sains Malaysia 11800 USM Penang Malaysia

ISBN: (数字)9781728152493

ISBN: (纸本)9781728152509

Engineering drawings contain many curves that intersect at a complex junction. detection of these junctions is vital for correct recognition of line drawings. In this paper we study the detection of junctions in document images. A threestage junction detection is proposed to detect junctions in document images. The first stage works at the pixel level. Any pixel with more than two neighbors is labeled as low-level-junction. The second stage works at connected component level. All low-level-junctions adjacent to other low-level-junctions are merged into mid-level-junctions. The third stage combines mid-level-junction at a distance less than a threshold into a high-level-junction. Experimental results on real scanned images of mechanical engineering drawings show a precision rate of 82.38% and a recall rate of 97.29%.

关键词： Junctions Computer science detection algorithms Software engineering Image edge detection Engineering drawings Microsoft Windows

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Ground RFI detection System for Passive Microwave Earth Observation Data and Space Missions

Ground RFI Detection System for Passive Microwave Earth Obse...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Roger Oliva Raul Onrubia Antonio Martellucci Elena Daganzo-Eusebio Flávio Jorge Stephen English Patricia de Rosnay Peter Weston Jose Barbosa Ioannis Nestoras Zenithal Blue Technologies European Space Agency European Centre for Medium-Range Weather Forecasts Research and Development in Aerospace GmbH

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Radio Frequency Interference (RFI) is a serious constraint affecting the Earth Observation (EO) passive microwave missions whose effect has been increasing. There is no single algorithm that can detect all RFI instances. The best strategy always is to combine several detection methods. This paper presents a new system concept: Ground RFI detection System (GRDS). The GRDS uses a wide variety of RFI detection algorithm to clean the Earth Observation measurements from RFI. The system architecture is modular and it is built to be able to scan for RFI for any EO mission. The initial assessments reported show the potential for this GRDS system.

关键词： detection algorithms Radiofrequency interference Microwave radiometry Libraries Databases Weather forecasting Sea measurements

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A Linear Complexity SCMA detection Algorithm

A Linear Complexity SCMA Detection Algorithm

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International Conference on Communication Technology (ICCT)

作者： Chengxin Jiang Yafeng Wang Key Laboratory of Universal Wireless Communications Beijing University of Post and Telecommunications Beijing China

ISBN: (数字)9781728181417

ISBN: (纸本)9781728181424

Sparse Code Multiple Access (SCMA) is a promising non-orthogonal multiple access scheme. Although message passing algorithm (MPA) can reduce the detection complexity exploiting the sparsity of SCMA, it is still exponential order. Excessive detection complexity is a major obstacle to SCMA engineering applications. In this paper, based on expectation propagation algorithm (EPA), a linear order complexity SCMA multi-user detection algorithm Max-Log-EPA is proposed. The average block error rate (BLER) simulation results prove that the proposed algorithm has a slight performance loss at low signal-to-noise ratio (SNR), while there is almost no performance loss at high SNR. This indicates that the proposed algorithm can significantly reduce the detection complexity with only a slight performance loss, which greatly promotes the engineering application of SCMA scheme.

关键词： Complexity theory Decoding Uplink Receiving antennas 5G mobile communication NOMA detection algorithms

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A Hierarchical Failure Detector Based on Architecture in VANETs

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IEEE ACCESS 2019年 7卷 152813-152820页

作者： Liu, Jiaxi Ding, Fei Zhang, Dengyin Nanjing Univ Posts & Telecommun Jiangsu Key Lab Broadband Wireless Commun & Inter Nanjing 210003 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing 210003 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Nanjing Peoples R China

The failure detector is one of the fundamental components for maintaining high availability of Vehicular Ad-hoc Networks (VANETs). However, the dynamic nature of VANETs caused by the high mobility of vehicles and communication link failures has a serious impact on the performance of failure detection. Therefore, it is very meaningful to design a suitable failure detector that can deal with the dynamic nature of VANETs well. In this paper, we propose a hierarchical failure detector based on the architecture of VANETs. This failure detector can adapt to the dynamic network conditions and meet the different Quality of Service (QoS) requirements of multiple applications in VANETs. Different from existing failure detectors, we propose a failure detector that employs a detection-result sharing mechanism and groups the nodes according to the architecture of VANETs. We evaluate our proposed failure detector by using NS2 and GT-ITM to simulate the work environment of VANETs. The experimental result shows that our proposed failure detector can improve the detection time by at most 45 and the detection accuracy by at most 25 under similar detection overhead.

关键词： Detectors Quality of service detection algorithms Protocols Topology Measurement Ad hoc networks VANETs hierarchical failure detection architecture QoS

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Hyperspectral Target detection by Fractional Fourier Transform

Hyperspectral Target Detection by Fractional Fourier Transfo...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Xiaobin Zhao Wei Li Tao Shan Lu Li Ran Tao School of Information and Electronics Beijing Institute of Technology China School of Automation Beijing Information Science and Technology University Beijing China

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Target detection in hyperspectral images (HSI) is an important technique and many target detection algorithms have been developed in recent years. The most widely detection algorithms by the original spectral characteristics may lack the ability of target signal enhancement and background suppression. This paper presents an efficient algorithm for detecting hyperspectral targets based on fractional Fourier transform (FrFT). Firstly, fractional Fourier transform primary search is used as preprocessing to obtain the better intermediate domain features with complementary characteristics between the original reflection spectrum and the Fourier transform domain. Secondly, fractional Fourier transform secondary search and constrained energy minimization (FrFT-CEM) was adopted to find an optimal fractional order to distinguish the target from the background. The proposed method has been proved to be superior in two real hyperspectral data sets.

关键词： Hyperspectral imaging Object detection Fourier transforms Feature extraction Detectors Anomaly detection detection algorithms

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Comparative Analysis of Various Approaches for DoS Attack detection in VANETs

Comparative Analysis of Various Approaches for DoS Attack De...

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Electronics and Sustainable Communication Systems (ICESC), 2020 International Conference on

作者： A. Ilavendhan K. Saruladha Pondicherry Engineering College Pondicherry India

ISBN: (数字)9781728141084

ISBN: (纸本)9781728141091

VANET plays a vital role to optimize the journey between source and destination in the growth of smart cities worldwide. The crucial information shared between vehicles is concerned primarily with safety. VANET is a MANET sub-class network that provides a free movement and communication between the RSU and vehicles. The self organized with high mobility in VANET makes any vehicle can transmit malicious messages to some other vehicle in the network. In the defense horizon of VANETs this is a matter of concern. It is the duty of RSU to ensure the safe transmission of sensitive information across the Network to each node. For this, network access exists as the key safety prerequisite, and several risks or attacks can be experienced. The VANETs is vulnerable to a range of security attacks including masquerading, selfish node attack, Sybil attack etc. One of the main threats to network access is this Denial of Service attack. The most important research in the literature on the prevention of Denial of Service Attack in VANETs was explored in this paper. The limitations of each reviewed paper are also presented and Game theory based security model is defined in this paper.

关键词： Vehicular ad hoc networks Computer crime Roads Safety detection algorithms Bandwidth

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k-Truss Network Community detection

k-Truss Network Community Detection

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Ian McCulloh Onur Savas Accenture Washington DC United States

ISBN: (数字)9781728110561

ISBN: (纸本)9781728110578

We review the k-truss algorithm for community detection in networks. The k-truss is an efficient clustering algorithm that holds advantageous properties for many network applications. In this paper, we compare the k-truss performance against other, more well-known community detection algorithms. The k-truss is uniformly more computationally efficient than the Louvain and Clauset-Newman-Moore algorithms in terms of speed and memory with comparable modularity. Potential applications are discussed.

关键词： Social networking (online) Image edge detection Layout Memory management Clustering algorithms Computational efficiency detection algorithms

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A Comparative Study of Deepfake Video detection Method

A Comparative Study of Deepfake Video Detection Method

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International Conference on Information and Communications Technology (ICOIACT)

作者： Kurniawan Nur Ramadhani Rinaldi Munir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia School of Computing Telkom University Bandung Indonesia

ISBN: (数字)9781728173566

ISBN: (纸本)9781728173573

Deepfake technology allows humans to manipulate images and videos using deep learning technology. The results from deepfakes are very difficult to distinguish using ordinary vision. Many algorithms are built to detect deepfake content in images and videos. There are several approaches in deepfake detection, including a visual feature-based approach, a local feature-based approach, a deep feature-based approach and a temporal feature-based approach. The main challenge in developing deepfake detection algorithms is the variety of existing deepfake models in both images and videos. Another challenge is that deepfake technology is still evolving, making deepfake images and videos look more realistic and harder to detect.

关键词： Visualization Feature extraction Pattern recognition Information and communication technology detection algorithms Videos Information integrity

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