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检索条件"任意字段=2022 2nd International Conference on Detection Technology and Intelligence System, DTIS 2022"

共 1121 条记录，以下是51-60 订阅

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Research on Key technology of Interactive Animation Design Combined with Artificial intelligence technology 2

Research on Key Technology of Interactive Animation Design C...

引用

2nd international conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Gao, Yingwei Changchun University of Architecture and Civil Engineering College of Cultural and Creative Industries Changchun China

ISBN: (纸本)9798350386639

Most of the existing character animation generation algorithms introduce motion capture data matching the skeleton, which cannot adapt to the complex and changeable skeleton and dynamic scene requirements. This project intends to study the reconstruction method of mobile capture data for multiple arbitrary skeleton topologies. The character path modeling based on 3D dynamic path search and sound human-machine interface are used to replace the traditional GUI to complete the realistic movement of characters in 3D environment. In order to build an interactive Web VR environment based on Shout3D, its working process is divided into four stages: modeling, output, editing and publishing. The model is generated by Shout3D's professional output plug-in or third-party format conversion software. The experimental results show that the algorithm can generate realistic, smooth and realistic character actions, and reduce the production cost while ensuring data reuse, so as to better adapt to the needs of various three-dimensional scenes. © 2024 IEEE.

关键词： Musculoskeletal system

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Human detection in Aerial Images using Deep Learning Techniques 2

Human Detection in Aerial Images using Deep Learning Techniq...

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2nd international conference on Artificial intelligence and Signal Processing, AISP 2022

作者： Gundu, Sireesha Syed, Hussain Harikiran, J. School of CSE VIT-AP University Andhra Pradesh India

ISBN: (纸本)9781665442909

Activity recognition in drone-based surveillance is related to many computer vision problems such as pose estimation, object detection, image retrieval, face recognition, frame tagging in videos, and video action recognition. In a drone-based surveillance system, detection and recognition of human activities in a single frame is a challenging task as the clips are shot from an aerial view. Unlike activity recognition in static camera-captured videos where spatio-temporal features are utilized, they are not utilized in drone-captured images. This problem is addressed in this paper using HOG and Mask-RCNN. Experimental results show that the proposed method can be obtained more accurate results in many drone-based frames. This work produces high-quality segmentation through instance segmentation in addition to the histograms gradient-based method and also improves the accuracy of object detection in aerial images and gives the best classification results. © 2022 IEEE.

关键词： Drones

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Performance Analysis of Optical-SAR Cooperative system Based on Mutual Information 2

Performance Analysis of Optical-SAR Cooperative System Based...

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2nd IEEE international conference on Signal, Information and Data Processing, ICSIDP 2024

作者： Wang, Chonghang Xu, Huaping Zhou, Zihan Li, Chunsheng Li, Wei Xu, Liying Beihang University School of Electronic and Information Engineering Beijing China Shanghai Institute of Satellite Engineering Shanghai China

ISBN: (纸本)9798331515669

The current research on optical-SAR cooperative work mainly focuses on the fusion of optical and SAR images, while there are fewer studies on how the optical and SAR sensor can cooperate optimally for targets survey. In this paper, mutual information is employed as the evaluation metric of optical-SAR cooperative system. Firstly, the optical-SAR cooperative system is modeled according to imaging principles. Then the mutual information expression of the optical-SAR cooperative system is derived with the stochastic process theory. Finally, through simulation, the relationship between the mutual information of the cooperative system and the target detection probability is analyzed to verify the validity of the mutual information as the performance evaluation metric of the cooperative detection system. © 2024 IEEE.

关键词： detection mutual information Optical-SAR Collaborative system performance evaluation

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Damage detection system of Ancient Paper Books Based on Machine Vision 2

Damage Detection System of Ancient Paper Books Based on Mach...

引用

2nd international conference on Algorithms, High Performance Computing and Artificial intelligence, AHPCAI 2022

作者： Wang, Hong Sun, Shaoming Kan, Tao Sun, Genji Hefei Institutes of Physical Science Chinese Academy of Sciences Anhui Hefei230031 China University of Science and Technology of China Anhui Hefei230026 China Zhongke Hefei Institute of Technology Innovation Engineering Anhui Hefei230088 China

ISBN: (纸本)9798350334784

In order to improve the intelligence of paper ancient books restoration and reduce the consumption of manpower and material resources, the machine vision detection technology is proposed to detect the damaged area of ancient books surface. In this paper, the experiment is carried out on the system platform that has been built to detect and repair the damage of ancient paper books. Based on the damaged paper obtained from the system platform, image denoising, image binarization, edge detection and other operations are carried out to obtain the contour position information of the damaged area, which provides data support for the generation of the motion track required by the system, so as to complete the whole repair work of ancient books. Furthermore, the application interface is developed using Qt. After testing, the application has good effect and fast speed in detecting damaged areas of ancient books, meeting the needs of actual use. © 2022 IEEE.

关键词： Computer vision

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The Object-Centric Anomaly detection for Aero-engine Blade 24

The Object-Centric Anomaly Detection for Aero-engine Blade

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2nd international conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Lv, Xinwei Chen, Haiyong Qi, Xuan Wang, Yining Li, Dongying Zhang, Xingshun Zhang, Haode School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China

ISBN: (纸本)9798400710681

Industrial Anomaly detection (IAD) focuses on the real-time identification of various deviations that affect product quality, such as appearance defects, dimensional inaccuracies, or material performance issues. By providing timely corrections, IAD effectively reduces the defect rate and significantly enhances product quality. However, most existing IAD research assumes that training and test data are derived from the same distribution, which often poses challenges in real-world applications. The experimental dataset highlights two major issues: the inconsistency and scale differences of target samples, and the significant distribution shifts in test data caused by variations in illumination, pose, or background, which greatly diminish the effectiveness of traditional IAD methods. To address the anomaly detection challenges posed by distribution shifts. The innovation lies in introducing a dual-view mechanism coupled with an asymmetric masking rate of up to 95%, effectively mitigating dependency on dataset diversity. Additionally, we propose a novel robust AD strategy that involves masking the vast majority of the future frame regions while keeping past frames unchanged. This approach encourages the network to focus on object dynamics, extracting object-centric representations. During training, we adopt an unsupervised approach, aiming to minimize the differences between distributions and among OOD normal samples, to address the diverse distribution shifts and ensure the robustness and accuracy of detection results. © 2024 Copyright held by the owner/author(s).

关键词： Turbomachine blades

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Intrusion detection in Network Security 2

Intrusion Detection in Network Security

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2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2022

作者： Wang, Ru-Xin Wang, Yi Dai, Lei School of Xinjiang Institute of Technology School of Economics Trade and Management Aksu Xinjiang735400 China

ISBN: (纸本)9781510663107

With the development of computer network technology, the risk of network intrusion also increases greatly. But the traditional encryption and firewall technology can not meet the security needs of today. Therefore, intrusion detection technology is a new dynamic security mechanism developed rapidly in recent years. This paper studies the security mechanism used to detect and prevent system intrusion. Different from the traditional security mechanism, intrusion detection has the characteristics of intelligent monitoring, real-time detection, dynamic response and so on. In a sense, intrusion detection technology is a reasonable complement to firewall technology. © 2023 SPIE.

关键词： Intrusion detection

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A detection Method for Local Wire Bond Failure in IGBT Based on High-Frequency Time-Domain Reflective Signal Response Analysis 2

A Detection Method for Local Wire Bond Failure in IGBT Based...

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IEEE 2nd international conference on Power Science and technology (ICPST)

作者： Xie, Wangyu Liu, Chang Wang, Weijie Xiang, Chaoqun Yuan, Weiyu Cheng, Shu China Acad Railway Sci Co Ltd Locomot & Car Res Inst Beijing Peoples R China Beijing Zongheng Electromech Technol Co Ltd Beijing Peoples R China Cent South Univ Traff & Transportat Engn Changsha Peoples R China

ISBN: (纸本)9798350349047;9798350349030

Wire bond lift-off and fracture are the main causes of failure in power semiconductor devices, with IGBT being a representative example. The key external characteristic of such failures is an increase in impedance fluctuations. Therefore, this paper utilizes the spread spectrum time-domain reflectometry (SSTDR) signal possessing impedance response characteristics as the detection carrier for device features. By constructing an equivalent impedance model for IGBT chip wire bond failures, a fault detection method based on the mapping correlation between signal response characteristics and wire bond failure features is proposed. Experimental results demonstrate the capability of this method to assess the level of local wire bond failures, and the test results align with theoretical analysis.

关键词： Time-domain reflective signal IGBT wire bond liftoff impedance characteristics fault detection

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2nd international conference on Information technology, InCITe 2022

2nd International Conference on Information Technology, InCI...

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2nd international conference on Information technology, InCITe 2022

ISBN: (纸本)9789811973451

The proceedings contain 72 papers. The special focus in this conference is on Information technology. The topics include: Recommender system Based on Network Structure Link Analysis Technique Through Community detection in Social Network to Handle the Cold-Start Problem;Performance Analysis of NOMA Over Hybrid Satellite Terrestrial Communication systems;multivariate Partially Blind Signature Scheme;topic Analysis and Visualisation of Peer-to-Peer Platform Data: An Airbnb Case Study;pandemic-Induced Behavioral Change in Mobile Banking Adoption: An Opportunity for Indian Banking Industry for Embracing Artificial intelligence;on the Efficacy of Boosting-Based Ensemble Learning Techniques for Predicting Employee Absenteeism;framework to Impute Missing Values in Datasets;modelling of an Efficient system for Predicting Ships’ Estimated Time of Arrival Using Artificial Neural Network;a Critical Review on Search-Based Security Testing of Programs;Deep Learning-Based Black Hole detection Model for WSN in Smart Grid;feature Selection Methods for IoT Intrusion detection system: Comparative Study;Reformed Binary Gray Wolf Optimizer (RbGWO) to Efficiently Detect Anomaly in IoT Network;a Feature-Based Recommendation system for Mobile Number Portability;An Efficient Deep Learning Model FVNet for Fingerprint Verification;microcalcification detection Using Ensemble Classifier;classification and Prediction of Financial Datasets Using Genetic Algorithms;stratified Alignment Using Attention Mechanism for Video Captioning;an IoT-Based Efficient Water Quality Prediction system for Aquaponics Farming;cluster-Based Congestion Avoidance and Data Aggregation Routing in Wireless Sensor Networks;Relevance Vector Machine Tools for Evaluating the Strength Parameters of HPC Incorporating Quarry Dust and Mineral Admixtures with Fibers;Video Forgery detection and Localization with Deep Learning Using W-NET Architecture.

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A high-accuracy ensemble method of convolutional neural networks for damaged building detection on post hurricane satellite images 2

A high-accuracy ensemble method of convolutional neural netw...

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2022 2nd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2022

作者： Zhang, Zhiyang Faculty of Information Technology Macau University of Science and Technology Taipa China

ISBN: (纸本)9783800760268

After hurricane disasters, rapid damage assessment is critical to ensure an effective response. However, the current method for building damage assessment requires intense time and human resources. The emerging high-resolution optic satellite, computer vision, and machine learning techniques could help improve the efficiency of damage assessment. In this work, an ensemble method of convolutional neural network was proposed for high accuracy of automatic damaged building detection of post-hurricane satellite images. The customized convolution neural network, deep learning architectures of random initialization and transfer learning were trained separately. Then a model average ensemble was introduced to avoid overfitting and further increase the detection accuracy. The hurricane Harvey dataset consisting of 23000 images has been used in this paper for training and testing. The experiment results illustrated that the ensemble model can achieve very high accuracy above 99% on both balance and unbalanced test datasets, outperforming all the previously published results. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Deep learning

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Research on artificial intelligence logistics distribution route management system based on computer information technology 2

Research on artificial intelligence logistics distribution r...

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2nd international Signal Processing, Communications and Engineering Management conference, ISPCEM 2022

作者： Zhang, Zhishuai School of Management Tianjin University of Technology Tianjin China

ISBN: (纸本)9781665492713

This paper introduces two shortest path algorithms under computer information technology, and introduces some applications of them in logistics management. Dijkstra algorithm and Floyd algorithm are used to solve the distribution path problem in logistics management, and compare the two algorithms. In order to ensure that in the future practice, the fit, adaptability and compatibility of artificial intelligence technology (AI) can be reasonably developed, so as to provide technical support for optimizing the network structure and enhancing the network operation effect. Combined with the current situation and needs of data analysis of logistics enterprises, it provides decision support for logistics enterprises to improve logistics marketing services and optimize logistics routes. © 2022 IEEE.

关键词： Artificial intelligence

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