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检索条件"任意字段=8th IEEE International Conference on Software Engineering and Computer Systems, ICSECS 2023"

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Deep learning for speech emotion recognition: A technical tutorial on the state of the art 8

Deep learning for speech emotion recognition: A technical tu...

引用

8th international conference on Information systems engineering, ICISE 2023

作者： Liu, Hai Li, Jiawen Zhao, Li Si, Junya Li, Weixin Shen, Dazhen Li, Zixin Liu, Tingting Wuhan Donghu University School of Computer Science Wuhan430212 China

ISBN: (纸本)9798350307009

Speech is the simplest, most natural and most direct way of communication between people, and the rise of smart devices makes speech emotion recognition (SER) technology the most important part of human-computer interaction (HCI). this paper will start from the concept of language emotion recognition, and research the systematic research on speech emotion recognition in five aspects. First, we review the classification of some phonetic emotional features. Secondly, we introduce some of the latest technologies for speech emotion recognition based on traditional and machine learning. Furthermore, we summarize the classification of some common datasets. Finally, we discuss the practical application and future research direction of speech emotion recognition. © 2023 ieee.

关键词： Classification (of information)

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Object Detection and Recognition System Using Deep Learning Method 8

Object Detection and Recognition System Using Deep Learning ...

引用

8th ieee international conference for Convergence in Technology, I2CT 2023

作者： Railkar, Yashal Nasikkar, Aditi Pawar, Sakshi Patil, Pranjal Pise, Rohini Pimpri Chinchwad College of Engineering India

ISBN: (纸本)9798350334012

Object detection has been studied by many researchers for important applications in the industry like detecting a road object for self-driving cars, medical research for detecting particular diseases, gesture control, etc. Object detection and recognition is incredibly very important wrt security purposes. As computers and models can work 24/7 it can watch for video surveillance in secure areas. Humans can quickly detect or make out what items are there in photos and photographs, where these images and pictures are located, and how they interact with systems when they see them. [1]. Object identification and tracking is a key challenge in CV systems and interactions, such as visual surveillance and human computer vision systems. Human visual systems are quick and precise, allowing them to handle complicated activities such as driving. computers will be able to drive automobiles using improvised and speedy errorfree object identification algorithms, yet they will require specialized sensors and auxiliary gadgets to relay real-time scenarios. [1]Using exact object recognition and picture classification approaches, strategies, and methodologies, it is critical and essential for deciding autonomous driving in metropolitan situations. Many big companies are currently working on this and achieving their goals day by day. In this report a object detection system has been proposed which can detect various objects, in fact it can detect almost any object wrt. training given to the model. Proposed methodology for object detection in the report is You Look Only Once (YOLO). © 2023 ieee.

关键词： Object detection

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CNN-LSTM-AE Based Predictive Maintenance Using STFT for Rotating Machinery 8

CNN-LSTM-AE Based Predictive Maintenance Using STFT for Rota...

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8th ieee/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2023

作者： Gong, Seokhyun Lee, Jaehyeong Lee, Chae-Gyu Jeong, Jongpil Choi, Wonmin Kim, Chanyoung Park, Jungsoo Kim, Jongheon Sungkyunkwan University Dept. Smart Factory Convergence Suwon16419 Korea Republic of Sungkyunkwan University Dept. Electronic and Electrical Engineering Suwon16419 Korea Republic of Sungkyunkwan University Dept. Mechanical Engineering Suwon16419 Korea Republic of Sungkyunkwan University Dept. Systems Management Engineering Suwon16419 Korea Republic of

ISBN: (纸本)9798350373615

In modern manufacturing after the Fourth Industrial Revolution, fast and accurate production is essential, and it is important to maintain and improve process reliability and productivity. Beyond the traditional conservative maintenance method, it is important to monitor the condition of facilities and take preventive measures. this study aims to analyze vibration data of manufacturing equipment and predict rotor defects using deep learning technology. An anomaly detection model that distinguishes between normal and abnormal conditions of the equipment is trained, and proactive problem prediction through internal and external data (sensor data, operation logs, etc.) is emphasized. Vibration data is converted into two-dimensional image data through Short Time Fourier Transform (STFT), and feature extraction is performed through Convolutional Neural Network (CNN) algorithm. then, an Autoencoder (AE) based time series anomaly detection technique is used to make efficient and accurate predictions. In order to strengthen the competitiveness of the manufacturing industry, a deep learning-based rotor defect prediction model was developed, which is expected to improve the stability and productivity of the manufacturing process. © 2023 ieee.

关键词： Defects

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Gaze estimation methods based on deep learning: Research status, challenge and future 8

Gaze estimation methods based on deep learning: Research sta...

引用

8th international conference on Information systems engineering, ICISE 2023

作者： Liu, Tingting Li, Zixin Zhao, Li Li, Weixin Si, Junya Liu, Hai Shen, Dazhen Li, Jiawen Wuhan Donghu University School of Computer Science Wuhan430212 China

ISBN: (纸本)9798350307009

Gaze estimation has been gaining countless currency in recent years, however, that is still confronted with myriad challenges. In the work, we present a brief overview of gaze-based applications, related methods and several dominant plight. First and foremost, we retrospect about the application on basis of gaze. Additionally, we classify the related method into three types: 3D Geometric model, monocular or binocular estimation and deep learning model. Subsequently, we summarize the main challenge, which is still a tough nut for researches to crack. Ultimately, we discuss about the research status and dilemmas for future researchers. © 2023 ieee.

关键词： computer vision

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Smart Contract-Based Multi-Stage Service Auction for Refraction Networks 8

Smart Contract-Based Multi-Stage Service Auction for Refract...

引用

8th international conference on computer and Communication systems, ICCCS 2023

作者： Shi, Xin Guo, Yunfei Wang, Yawen Tong, Yu Wu, Yanpeng Institute of Information Technology Information Engineering University Zhengzhou China

ISBN: (纸本)9781665456128

As a promising Internet censorship circumvention technique, refraction networks have attracted the wide attention of researchers in recent years. However, it remains a crucial issue to be tackled, i.e., how to motivate more service providers, known as decoy routers, and clients to join refraction networks, especially with guaranteed security and privacy. To address the issue, we develop a decentralized service auction framework based on the blockchain constructed through clients and decoy routers. Further, we design a multi-stage service auction (MSSA) smart contract composed of multiple functions and events, which are triggered and executed autonomously to complete the tasks, including registration, double auction, first-price sealed auction, and payment clearing. Moreover, we implement the designed MSSA smart contract in the Remix integrated development environment and run a test case on Ethereum virtual machines. the experiment results verify the modest gas and ether cost of the smart contract-based solution and its effectiveness. © 2023 ieee.

关键词： Smart contract

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CAKG: A Framework for Cybersecurity threat Detection of Automotive via Knowledge Graph 8

CAKG: A Framework for Cybersecurity Threat Detection of Auto...

引用

8th international conference on Data Science in Cyberspace, DSC 2023

作者： Yang, Peng Lijie, Wang Yun, Li Xuedong, Song Yaxin, Wang Biheng, Guo School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Cybersecurity Research Institute Guangdong Weichen Information Technology Co. Ltd Dongguan China

ISBN: (纸本)9798350331035

With the increasing complexity and connectivity of vehicles, ensuring their security has become a critical concern. In this study, we propose CAKG: A Framework For Cybersecurity threat Detection Of Automotive Via Knowledge Graph, achieved with a knowledge graph for vehicle vulnerability and threat intelligence. We integrate existing cyber security knowledge bases to analyze potential attack surfaces and scenarios specific to automobiles. By using keyword extraction and text similarity analysis, we identify threats relevant to the event produced by Intrusion Detection systems(IDS) in automotive. Moreover, we leverage another knowledge graph to analyze attack logs gained from actual vehicles, enabling us to further correlate security events and product situational analysis. Our framework provides a holistic perspective on vehicle security, facilitating threat modeling and enhancing our understanding of potential attack scenarios. © 2023 ieee.

关键词： Attack Graph Cybersecurity Knowledge Graph Intelligent Connected Vehicles threat Intelligence Vulnerability Analysis

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A Central High-speed Lane Routing Protocol for Flow-Guided Intra-body Nanonetworks 8

A Central High-speed Lane Routing Protocol for Flow-Guided I...

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Yao, Xin-Wei Lin, Lang Asghari, Masoud College of Computer Science and Technology Zhejiang University of Technology Hangzhou China University of Maragheh Faculty of Engineering Maragheh Iran

ISBN: (纸本)9781665456128

the development of nanotechnology in recent years makes intra-body flow-guided nanonetworks more feasible. Monitoring different biomarkers, detecting infectious agents, locating cancerous cells, delivering drugs accurately and other medical application are under study. Taking the consideration of the laminar blood flow feature of blood vessels, where concentric layers of blood with different velocities move along in the length of the vessels and the central layer (i.e., lane) has the highest velocity, this paper proposes a central high-speed lane routing protocol, which selects nano-nodes with high speed in the central layer of blood flow and forms a directional relaying chain for other non-central nano-nodes. this protocol helps improve the throughput and success rate of the nanonetworks with high node density and the utilization and life cycle of the nano-nodes. the protocol is simulated under the blood vessel model combined with laminar movement model in Nano-Sim platform, and has been proven its great performance. © 2023 ieee.

关键词： Blood

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Accuracy Evaluation of Stereo Visual SLAM with Unnecessary Feature Point Elimination Using Blur Processing for AR Surgical Support System 8

Accuracy Evaluation of Stereo Visual SLAM with Unnecessary F...

引用

8th international conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2023

作者： Koeda, Masanao Kaihara, Yuto Sawada, Atsuro Hamada, Akihiro Magaribuchi, Toshihiro Ogawa, Osamu Onishi, Katsuhiko Noborio, Hiroshi Okayama Prefectural University Faculty of Computer Science and Systems Engineering 111 Kuboki Soja-shi Okayama Japan Kyoto University Department of Urology Graduate School of Medicine 54 Shogoin-kawahara-cho Sakyo-ku Kyoto Japan Osaka Electro-Communication University Faculty of Information Science and Arts Kiyotaki 1130-70 Shijonawate Osaka Japan

ISBN: (纸本)9798350369564

In this study, we describe an evaluation of the positional accuracy of stereo Visual SLAM with noisy feature points removed by blurring. We constructed an experimental environment that intentionally degrades the accuracy of Visual SLAM. In this environment, we placed the objects that are likely to generate noisy feature points. We evaluated the accuracy of the estimated positions of the original video and the video in which blurred regions of noise in the original video were provided to Visual SLAM. Consequently, we confirmed that the accuracy was improved compared to that of the original video. © 2023 ieee.

关键词： Stereo image processing

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Research on Lightweight Model-Based Leather Defect Edge Inference Mechanism 8

Research on Lightweight Model-Based Leather Defect Edge Infe...

引用

8th international conference on Intelligent Computing and Signal Processing, ICSP 2023

作者： Xiao, Wen Wang, Meilin He, Jiaxian Feng, Zhipeng Guangdong University of Technology School of Information Engineering Guangzhou China

ISBN: (纸本)9798350302455

Real-time and accurate detection of production defects is one of the most critical aspects of the production process. this paper proposes a model lightweight-based edge inference mechanism for leather defect detection. By collecting thousands of samples of leather defects and creating a self-made dataset. then train the model through the YOLO algorithm. Constraining the size of the channel factor γ and adding an L1 regular term about the γ to the target equation, so that it can be thinned and automatically pruned during training process. the pruning model is retrained on the self-made dataset by the weight of the pruning model, and the gradient descent algorithm is used to fine-tune the model to restore the accuracy, and then deployed on the edge device to perform inference detection on the real-time production picture of leather. the detection results are transmitted to the industrial control host computer for storage and screening, achieving real-time detection, classification, and display of defects in leather production. Compared with traditional defect detection systems, this paper achieves faster and more effective leather defect detection in the production process. © 2023 ieee.

关键词： Leather

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Game-Based Task Offloading in Cloud-Edge-End Network 8

Game-Based Task Offloading in Cloud-Edge-End Network

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8th international conference on computer and Communication systems, ICCCS 2023

作者： Li, Jinxuan Liang, Qiongfang Li, Dongxu Liu, Yuan Zhang, Yang Guangzhou Power Supply Bureau Guangdong Power Grid Co. Ltd. Guangzhou510620 China School of Electronic and Information Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9781665456128

Mobile edge computing (MEC) is a key enabler for the next generation network by leveraging the cloud function to network edge and reducing costs required to transmit data to the cloud. In this paper, we consider a cloud-edge-end network, in which users subscribe services to the cloud, and the cloud delegates the services to edge servers since they can support time-sensitive applications locally. All the cloud, edge servers, and users intend to maximize their utilities. To model the dynamic interactions among cloud-edge-end, we propose a hierarchical dynamic game framework. Specifically, in the lower-level game, the offloading decisions of users are modeled as an evolutionary game. In the upper-level game, considering the users' dynamic selections, we model the pricing strategy of the cloud and resource allocations of the edge servers as a Stackelberg differential game. the equilibrium and the optimal strategies of the players in the game are derived. the simulation results validate the effectiveness of our designed reward operation mechanism. © 2023 ieee.

关键词： Economics

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