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共 1872 条记录，以下是201-210 订阅

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Bangladeshi Local Vehicle recognition with A Comprehensive Dataset using Transfer Learning Techniques 4

Bangladeshi Local Vehicle Recognition with A Comprehensive D...

引用

4th international conference on Sustainable Technologies for Industry 4.0, STI 2022

作者： Rahman, Md Sazedur Hassan, Md Zahim Hossain, Syed Nahin Masrur, Noor Rabbi, Jakaria Khulna University of Engineering & Technology Dept of Computer Science and Engineering Bangladesh

ISBN: (纸本)9781665490450

Vehicle detection, localisation, and classification are essential for developing an intelligent Transport System (ITS). Bangladesh is a developing nation, and the number of vehicles here is increasing significantly each year. therefore, the development of an intelligent transportation system has become crucial. In order to assess the models' performance and the dataset's suitability for the task, we developed a demanding dataset of Bangladeshi vehicles and trained a variety of pre-trained models using it. the dataset contains 12,413 images of 9 most common local vehicle types of *** carefully examined the performance of the model on the image database. We proposed a model that provides the most accurate results for the localization, and categorization tasks of Bangladeshi vehicles. the study also indicates that the newly introduced dataset is more challenging and offers more similar scenarios that resembles real life situations than pre-existing datasets. © 2022 IEEE.

关键词： intelligent systems

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Design of Face recognition Alarm System Based on LBPH Algorithm

Design of Face Recognition Alarm System Based on LBPH Algori...

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Digital Society and intelligent systems (DSInS), international conference on

作者： Zhenzhen Li Jiaqing Zhou Officers College of PAP Chengdu China

ISBN: (数字)9798331528829

ISBN: (纸本)9798331528836

Keeping up with the advent of the wave of the network big data information age, there are more and more security risks in information security. this paper focuses on the alarm system of face recognition, using Python, OpenCV, HOG directional gradient histogram and QT interface. the content required for face recognition by electronic machinery and computer machines was analyzed. the HOG directional gradient histogram was used to recognize the face, and the feature vector was converted into face data. It realizes the function of timely alarm at the first time after face recognition; It achieves the purpose of face recognition and personnel identity authentication and timely alarm when non-insider personnel are detected.

关键词： Histograms Databases Face recognition Information security Alarm systems Information age Vectors Personnel Machinery intelligent systems

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Identification of PMSM Moment of Inertia based on Model Reference Adaptive Algorithm 4

Identification of PMSM Moment of Inertia based on Model Refe...

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4th IEEE international conference on Power, intelligent Computing and systems, ICPICS 2022

作者： Ding, Fan Zhang, Tao Jia, Danping Zhang, Hualiang Pei, Quanshen Huang, Haoran School of Information Science and Engineering Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences School of Electrical Engineering Dalian University of Technology Dalian China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665467735

ISBN: (纸本)9781665467735

A method that can identify the rotational inertia in a timely manner is proposed because the performance of a permanent magnet synchronous motor servo system is easily affected by the rotational inertia. Firstly, principles of model-referenced adaptive recognition algorithm is introduced, and the influence of the adaptive gain on the identification results is analyzed. then, design a suitable range of adaptive gain value, use the set error value to compare the identification error with the set value, and then select the appropriate gain for identification. Finally, through simulation verification, this method has fast identification convergence speed, high precision and strong anti-disturbance. © 2022 IEEE.

关键词： Adaptive algorithms

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Research on Virtual College English Learning Aid System of Computer intelligent Campus 4

Research on Virtual College English Learning Aid System of C...

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4th international conference on Computers, Information Processing and Advanced Education, CIPAE 2023

作者： Jin, Xiang Zhao, Zhijian Nanjing Engineering Branch Jiangsu Union Technical Institute Nanjing China

ISBN: (纸本)9798350342710

this paper proposes a virtual system for college English vocabulary assisted learning based on B/S computer. then an image recognition method based on word context vector similarity matching and CNN+BLSTM is proposed to improve the efficiency of word retrieval algorithm. the functional elements and technical requirements of communication AIDS such as recording, storage and playback are realized by using the microcontroller ATmega16L, MMC memory card and VS1003 audio chip. the system includes word learning module, listening learning module, reading and writing module, examination guide and excellent students' secret book module and edutainment module. the application results show that the system can realize the interaction between teachers and students before class, during class and after class, and close the connection between teachers and students. this system improves students' interest in foreign language learning and effectively promotes the improvement of teaching quality. © 2023 IEEE.

关键词： Learning systems

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Research on intelligent customs declaration generation in Guangdong-Hong Kong cross-border road cargo clearance 4

Research on intelligent customs declaration generation in Gu...

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4th international conference on Computer Science and Communication Technology, ICCSCT 2023

作者： Han, Chengguo Wang, Bin School of Management Guangdong University of Science and Technology Guangdong Dongguan523083 China Shenzhen Taizhou Technology Co. Ltd. Guangdong Shenzhen518031 China

ISBN: (纸本)9781510671232

Due to the uniqueness of "one country, two systems" and "two customs territories" in Guangdong (GD) and Hong Kong (HK), cross-border road cargo clearance between the two regions requires the creation of several documents. these include the Road Cargo Manifest, Vehicle Declaration, Customs Declaration, HK Seamless, HK Bundle, and HK Customs Declaration, as well as additional documents such as Packing List, Contract, and more. the use of Artificial intelligence (AI) can streamline the process of generating these documents and ensure accuracy and efficiency in cross-border road cargo clearance operations. this paper focuses on four aspects: text scanning and recognition, extraction of commodity classification declaration elements, conversion of customs declaration documents, and intelligent commodity classification. these areas of research aim to address the time-consuming and labour-intensive process of document creation and verification. By leveraging AI technologies, such as optical character recognition (OCR), data extraction algorithms, and machine learning (ML), it is possible to automate and optimize the production and review of these documents, thereby reducing time and manpower costs in cross-border road cargo clearance operations between GD and HK. Based on big data analysis of customs declaration documents from both regions, AI technologies such as feature extraction and machine learning can be utilized to achieve automation in the identification of documents like road cargo manifests and customs declarations. this research applied to the China international Trade Single Window (Shenzhen) and significantly improved the efficiency and accuracy of customs declaration in GD and HK. © 2023 SPIE.

关键词： international trade

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1st international Virtual conference on Visual pattern Extraction and recognition for Cultural Heritage Understanding (VIPERC 2022) 1

1st International Virtual Conference on Visual Pattern Extra...

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1st international Virtual conference on Visual pattern Extraction and recognition for Cultural Heritage Understanding, VIPERC 2022

作者： Amelio, Alessia Montelpare, Sergio Ursino, Domenico InGeo University "G. d’Annunzio" Chieti-Pescara Viale Pindaro 42 Pescara65127 Italy DII Marche Polytechnic University Via Brecce Bianche 12 Ancona60131 Italy

this document introduces the 1st international Virtual conference on Visual pattern Extraction and recognition for Cultural Heritage Understanding (VIPERC 2022), a premier forum for presenting the state-of-the-art, new research, ongoing work, academic and project reports in advanced statistics and machine learning, 3D modelling and simulation, knowledge representation, intelligent systems, information retrieval and software engineering, for visual pattern extraction, analysis and recognition to preserve the cultural heritage. © 2022 Copyright for this paper by its authors.

关键词： 3D modeling

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intelligent Customer Service System of Subway Based on Semantic Decision-Making Judgment

Intelligent Customer Service System of Subway Based on Seman...

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Machine Learning and intelligent systems Engineering (MLISE), international conference on

作者： Xinyu Liu School Of Urban Railway Transportation Shanghai University of Engineering Science China

ISBN: (数字)9798350375077

ISBN: (纸本)9798350375084

this study introduces an intelligent customer service system for urban rail transit, addressing inefficiencies and high labor costs in existing systems' problem classification and feedback mechanisms. Leveraging semantic understanding, the system integrates advanced speech recognition, intention classification, and entity extraction to automate the processing and intelligent classification of passenger hotline calls. Post-evaluation, the system demonstrated a minimum of 4.55% enhancement in data processing accuracy and F1 score, respectively, validating its efficacy in enhancing efficiency and precision. Furthermore, the research delves into the practical application of entity recognition, offering insights into the integration of natural language processing in intelligent customer service systems.

关键词： Rails Customer services Semantics Decision making Speech recognition Machine learning Data processing

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Automatic Detection and recognition Method of Digital Instrument Representation 4

Automatic Detection and Recognition Method of Digital Instru...

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4th international conference on intelligent Autonomous systems (ICoIAS)

作者： Liu, Jiale Wu, Huaiyu Chen, Zhihuan Wuhan Univ Sci & Technol Inst Robot & Intelligent Syst Jianshe 1st RdHeping Ave Wuhan 430081 Peoples R China

ISBN: (纸本)9781665441957

In order to automatically identify and monitor the display data of the existing digital meters, and improve the automation level of industrial meters, an automatic identification method for the number of digital meters is proposed. this method first preprocesses the picture, uses the text detection algorithm CRAFT to locate the digital display area on the position of the digital display screen, and cuts and divides the individual characters, and finally uses the improved threading method to recognize and read the single digital characters., Get the specific indication of the meter. Experiments show that the algorithm is easy to implement, has high accuracy, and can basically meet the identification requirements of various meter numbers, and has certain guiding significance for the existing digital meter identification.

关键词： Digital instrument text detection CRAFT threading method character recognition

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Continuous Sub-prevalent Co-location pattern Mining 4th

Continuous Sub-prevalent Co-location Pattern Mining

引用

4th international conference on Spatial Data and Intelligence, SpatialDI 2023

作者： Wang, Qilong Chen, Hongmei Wang, Lizhen School of Information Science and Engineering Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9783031329098

Spatial co-location pattern represents a subset of spatial features whose instances are frequently located together in space. Sub-prevalent co-location pattern mining discovers patterns with richer spatial relationships based on star instance model instead of clique instance model. Further, discovering spatiotemporal sub-prevalent co-location pattern is important to reveal the spatiotemporal interaction between spatial features and promote the application of patterns. However, the methods for mining spatiotemporal sub-prevalent co-location pattern measure the interestingness of patterns by the frequency of patterns in time slice set, and ignore the duration of patterns which is an important spatiotemproal information in patterns. thus, this paper presents mining spatiotemporal sub-prevalent co-location pattern by considering the duration and the frequency of patterns. Specifically, a novel pattern, is proposed by defining the continuous sub-prevalent index. then, an efficient algorithm is designed to mine the proposed patterns by utilizing the anti-monotonicity of continuous sub-prevalent index to prune unpromising patterns. Extensive experiments on synthetic and real datasets verify the practicability of the proposed patterns and the effectiveness of the proposed algorithm. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Location

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Federated Learning paradigm in E-health systems: An overview 4

Federated Learning paradigm in E-health systems: An overview

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4th international conference on pattern Analysis and intelligent systems, PAIS 2022

作者： Sellamna, Abdellatif Boukhamla, Akram Zine Eddine Benkaddour, Mohammed Kamel University of Kasdi Merbah Laboratoire d'Intelligence Artificielle et des Technologies de l'Information Ouargla Algeria

ISBN: (数字)9781665461610

ISBN: (纸本)9781665461610

Every day, professionals generate and use massive healthcare data to save, treat and ameliorate the lives of patients. the healthcare industry has adopted cloud-based solutions to solve several problems in a cost-effective manner. therefore, privacy and security mechanisms should be deployed to protect valuable medical information from unauthorized access. Much of the work in literature in recent years has focused on using artificial intelligence techniques such as deep learning and federated learning to solve various problems in the health field. Federated learning (FL) is a special technique for machine learning for privacy preservation. this study aims to compare the traditional centralized training approach and FL to show the advantages of using FL in the medical field and prove that FL can be adopted for security and data latency in e-health systems. the results obtained showed the feasibility of FL when compared to traditional methods used in the aspect of securing data and latency in the medical field. © 2022 IEEE.

关键词： Cost effectiveness

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