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Vehicle Target Detection and Tracking in Complicated Scenes of Infrared Videos 10

Vehicle Target Detection and Tracking in Complicated Scenes ...

引用

10th international conference on Control, Automation and Information Sciences, ICCAIS 2021

作者： Chen, Changke Chen, Mingkai Yao, Ping University of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665440295

Optical image automatic recognition is widely used in the fields of the disaster relief, public security maintenance, biological disaster prevention and medical treatment, etc. It is common to accomplish the recognition task with Hungarian Algorithm and Kalman Filter Method over objects detected by deep neural networks. However, this method has large errors under the conditions where there is camera movement, image rotation or target occlusion. this paper aims to detect the vehicle targets and obtain their coordinates from the infrared aerial video data with two stages: target detection and target tracking. In the target detection stage, YOLOv5 is used as the backbone network for model training. then, in the target tracking stage, the following methods are designed and implemented based on the Hungarian Algorithm and Kalman Filter Method. First, data enhancement is designed to solve the problem of frame rotation and disturbance. Second, the appearance matching and variance verification methods are proposed to deal with the failure in prediction of target positions caused by camera movement. third, the hidden frame temporary storage method is proposed to solve the occlusion problem, whose results are further confirmed by appearance comparison. Finally, in the output stage, the brightest point of five sample points is selected as the target point. With these methods, the missing detection and false alarm rates decrease, and the trace of the same target in the same video can be obtained even in complicated scenes. In the experiments, compared with the baseline algorithm, the missing detection rate of the proposed algorithm in the validation set is decreased by approximately 26%, and the track continuity score is improved by approximately 8.5%. Meanwhile, the size of the final prediction model is about 100MB while the results can be obtained within several seconds, which can meet the demands of real-time deployment of mobile platforms. © 2021 IEEE.

关键词： Kalman filters

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Robust Zero Watermarking Algorithm for Medical Volume Data Based on LBP 10th

Robust Zero Watermarking Algorithm for Medical Volume Data B...

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10th KES international conference on Innovation in Medicine and Healthcare, KES-InMed 2022

作者： Liu, Wenyi Li, Jingbing Liu, Jing Ma, Jixin School of Information and Communication Engineering Hainan University Haikou570228 China Research Center for Healthcare Data Science Zhejiang Lab Hangzhou310058 China School of Computing and Mathematical Sciences University of Greenwich LondonSE10 9LS United Kingdom

ISBN: (纸本)9789811934391

With the gradual rise of telemedicine, a large number of images will be transmitted on the network during network consultation, which may cause privacy disclosure. How to more effectively ensure the information security of patients and the copyright of medical images has attracted great attention of scholars in relevant fields. this paper proposed a robust watermarking method for medical volume data based on local binary pattern (LBP) transformation. Firstly, taking the Medical Volume Data as the research object, the low frequency feature vector of the Medical Volume Data is extracted by combining local binary mode transform and discrete cosine transform. then hash perception was performed. Finally, we use zero watermark technology to embed the hash sequence and chaotic technology to encrypt watermark. Experimental prove that the proposed algorithm has strong anti-attack abilities. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Local binary pattern

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Adversarial Synthesis of Human Pose from Text 1

引用

42nd German conference on pattern recognition, DAGM GCPR 2020 held in parallel with 25th international Symposium on Vision, Modeling, and Visualization, VMV 2020 and 10th Eurographics Workshop on Visual computing for Biology and Medicine, VCBM 2020

作者： Zhang, Yifei Briq, Rania Tanke, Julian Gall, Juergen Computer Vision Group University of Bonn Bonn Germany Bonn-Aachen International Center for Information Technology RWTH-Aachen University Bonn Germany

ISBN: (数字)9783030712785

ISBN: (纸本)9783030712778

this work focuses on synthesizing human poses from human-level text descriptions. We propose a model that is based on a conditional generative adversarial network. It is designed to generate 2D human poses conditioned on human-written text descriptions. the model is trained and evaluated using the COCO dataset, which consists of images capturing complex everyday scenes with various human poses. We show through qualitative and quantitative results that the model is capable of synthesizing plausible poses matching the given text, indicating that it is possible to generate poses that are consistent with the given semantic features, especially for actions with distinctive poses. © 2021, Springer Nature Switzerland AG.

关键词： Generative adversarial networks

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Construction of Clothing pattern Database Platform Based on Digital Color Matching 10th

Construction of Clothing Pattern Database Platform Based on ...

引用

10th international conference on Frontier computing, FC 2020

作者： Ba, Yan Dalian Art College Dalian116600 China

ISBN: (纸本)9789811601149

To solve the problem of "color matching," which is an important factor in fashion pattern design, a scheme of intelligent processing with computer is proposed. the difficulties of pattern design include: multi-dimensional caused by many factors and exponential growth knowledge explosion caused by permutation and combination of these factors, incomplete and fuzzy expression of professional knowledge, etc. A database model is proposed to express the relationship between various patterns, and a mathematical model of clothing patterns is established by analyzing practical pattern matching scenes. In addition, according to the characteristics and advantages of pattern database, the query method is improved;that is, instead of using the current simple database query method in the expert knowledge system, Grover algorithm is used to achieve color matching search. the operation of the test system shows that the model has the advantages of fast, concise, scalable and robust. © 2021, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Database systems

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Understanding Power Transformer Current-Voltage (I-V) Lissajous pattern Under Different Faults

Understanding Power Transformer Current-Voltage (I-V) Lissaj...

引用

international conference on Condition Monitoring and Diagnosis, CMD

作者： Nanda Redha Arsya Suwarno A. Abu-Siada School of Electrical Engineering and Informatics ITB PT. PLN (Persero) Bandung Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia School of Electrical Engineering Computing and Mathematical Science Curtin University Perth Australia

ISBN: (数字)9788986510225

ISBN: (纸本)9798350353877

Condition-based maintenance (CBM) is a robust maintenance strategy suitable for high-criticality assets, including Power Transformers. Various measurements and tests are conducted by current industry practice to assess the condition of power transformers. One common method used to assess the mechanical integrity of transformers is Sweep Frequency Response Analysis (SFRA). SFRA testing is performed to detect any changes due to windings or core deformations. However, the main drawback of this method is its offline nature and the requirement for high level of expertise to analyze the results. Several studies have been conducted to address these challenges. One proposed solution in the literature is to employ Current-Voltage (I-V) Lissajous pattern as a fingerprint for operating transformers. the method requires voltage and current measurements at both sides of each phase at the power frequency. Hence, it has the potential to be implemented online whereas, any deviation from the fingerprint raises an alarm for potential internal faults. However, the literature lacks of a comprehensive study on the detailed impact of various faults on the proposed fingerprint. this paper is aimed to investigate the impact of various fault types and levels on the transformer I-V Lissajous pattern. In this regard, simulations have been conducted on a detailed high-frequency power transformer equivalent circuit using PSIM software tool. Results are aimed to provide insights to understand power transformers I-V Lissajous patterns under different faults. With clear understanding, the I-V Lissajous method can be widely applied for other critical assets in the power grid in the future.

关键词： Electric potential Deformation Current measurement Fingerprint recognition Capacitance Maintenance Power transformers Circuit faults Integrated circuit modeling Equivalent circuits

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An innovative business model for a multi-echelon supply chain inventory management pattern

An innovative business model for a multi-echelon supply chai...

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2020 international Symposium on Automation, Information and computing, ISAIC 2020

作者： Cesarelli, G. Scala, A. Vecchione, D. Ponsiglione, A.M. Guizzi, G. Department of Chemical Materials and Production Engineering University of Naples "Federico II" Piazzale Tecchio 80 10th sector Naples Italy Department of Public Health University of Naples "Federico II" School of Medicine Via Pansini 5 5th sector Naples Italy Department of Electrical Engineering and Information Technologies University of Naples "Federico II" Via Claudio 21 10th sector Naples Italy

Nowadays, companies are experimenting novel organizational solutions to efficiently operate in uncertain and highly dynamic scenarios. As a potential solution, this paper proposes a new business model for a multi-echelon Supply Chain inventory management pattern. Specifically, an inventory model with proactive lateral transshipments was developed and subsequently tested carrying out 288 experiments with the aim of assessing transshipments impact on the performance of a two-echelon Supply Chain. the final goal was to investigate the potential reduction of the overall cost of the enterprise and, conversely, whether this approach could promote significant improvements in the level of service, achievable through a more efficient management of resources. the analyses and simulations indicate the use of large batches and/or low-cost products did not demand the necessity of transshipment events. these preliminary findings could be potentially validated and tested in the future considering more complex networks or multiple products. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Complex networks

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10th international Advanced computing conference, IACC 2020

10th International Advanced Computing Conference, IACC 2020

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10th international Advanced computing conference, IACC 2020

ISBN: (纸本)9789811604003

the proceedings contain 65 papers. the special focus in this conference is on Advanced computing. the topics include: Energy-Aware Edge Intelligence for Dynamic Intelligent Transportation Systems;a Single Criteria Ranking Technique for Schools Based on Results of Common Examination Using Clustering and Congenital Weights;5G Software-Defined Heterogeneous Networks in Intra Tier with Sleeping Strategy;Performance Investigation of MIMO-OFDM Based Next Generation Wireless Techniques;DLC Re-Builder: Sketch Based recognition and 2-D Conversion of Digital Logic Circuit;Design of I/O Interface for DDR2 SDRAM Transmitter Using gpdk 180 nm Technology;Improved SMO Based on Perturbation Rate in Local Leader Phase;generation of Pseudo Random Sequence Using Modified Newton Raphson Method;smoothening Junctions of Engineering Drawings Using C2 Continuity;amur Tiger Detection for Wildlife Monitoring and Security;an Efficient Privacy Preserving Algorithm for Cloud Users;An Upper Bound for Sorting Rn with LRE;programmable Joint computing Filter for Low-Power and High-Performance Applications;novel Design Approach for Optimal Execution Plan and Strategy for Query Execution;an Iterative and Incremental Approach to Address Regulatory Compliance Concerns in Requirements Engineering;state Space Modeling of Earned Value Method for Iterative Enhancement Based Traditional Software Projects Tracking;agile Planning and Tracking of Software Projects Using the State-Space Approach;Classification of Plant Species with Compound and Simple Leaves Using CNN Fusion Networks;a Deep Learning-Based Transfer Learning Approach for the Bird Species Classification;Integration of Explainable AI and Blockchain for Secure Storage of Human Readable Justifications for Credit Risk Assessment;iSHAB: IoT-Enabled Smart Homes and Buildings.

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10th international Advanced computing conference, IACC 2020

10th International Advanced Computing Conference, IACC 2020

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10th international Advanced computing conference, IACC 2020

ISBN: (纸本)9789811604034

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Hidden pattern: Toward Decision Support Fuzzy Systems 10th

Hidden Pattern: Toward Decision Support Fuzzy Systems

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10th EAI international conference on Context-Aware Systems and Applications, ICCASA 2021

作者： Han, Nguyen Van Vinh, Phan Cong Phung, Bui Minh Dan, Tran Ngoc Faculty of Information Technology Nguyen Tat Thanh University 300A Nguyen Tat Thanh Street Ward 13 District 4 Ho Chi Minh City Viet Nam Faculty of Information Technology Van Lang University 45 Nguyen Khac Nhu Street Ward Co Giang District 1 Ho Chi Minh City Viet Nam 1018 To Ky Tan Chanh Hiep Ward District 12 Ho Chi Minh City Viet Nam

ISBN: (纸本)9783030931780

In this paper, we introduce a method for computing with words to find linguistic hidden pattern (LHP ) as well as decision support system (DSS ) based on hedge algebra (HA ) using linguistic cognitive map (LCM ). Our model consists of a set of vertices and edges whose values are linguistic variables that are constrained by a linguistic lattice. the algorithm for the system studied will convert to hidden pattern. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Wooden fences

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10th international conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021 held as Part of EvoStar 2021

10th International Conference on Artificial Intelligence in ...

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10th international conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021 held as Part of EvoStar 2021

ISBN: (纸本)9783030729134

the proceedings contain 31 papers. the special focus in this conference is on Artificial Intelligence in Music, Sound, Art and Design. the topics include: Identification of Pure Painting Pigment Using Machine Learning Algorithms;evolving Neural Style Transfer Blends;evolving Image Enhancement Pipelines;Genre recognition from Symbolic Music with CNNs;axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks;interactive, Efficient and Creative Image Generation Using Compositional pattern-Producing Networks;preface;sculpture Inspired Musical Composition: One Possible Approach;aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity;auralization of three-Dimensional Cellular Automata;chord Embeddings: Analyzing What they Capture and their Role for Next Chord Prediction and Artist Attribute Prediction;convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation;the Enigma of Complexity;SerumRNN: Step by Step Audio VST Effect Programming;parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks;raga recognition in Indian Classical Music Using Deep Learning;the Simulated Emergence of Chord Function;incremental Evolution of Stylized Images;network Bending: Expressive Manipulation of Deep Generative Models;dissecting Neural Networks Filter Responses for Artistic Style Transfer;a Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features;a Multi-objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation;exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks;"A Good Algorithm Does Not Steal – It Imitates": the Originality Report as a Means of Measuring When a Music Generation Algorithm Copies Too Much.

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