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共 2049 条记录，以下是211-220 订阅

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Misbehavior Detection in the Internet of Vehicles using Machine Learning based Situation Identification 8

Misbehavior Detection in the Internet of Vehicles using Mach...

引用

8th international conference on Communication and Electronics Systems, ICCES 2023

作者： Kelagadi, Hemantaraj M. Chandra Sekhar, Jampani Rawat, Ruchira Dhaliwal, Navdeep Singh, Swati Saravana, B. Shanthi Kle Technological University School of Electronics and Communication Engineering Karnataka Hubballi India Nri Institute of Technology Department of Computer Science and Engineering Andhra Pradesh Guntur India Graphic Era Deemed to Be University Department of Computer Science and Engineering Uttarakhand Dehradun India Lovely Professional University Division of Research and Development Punjab Phagwara India Uttaranchal University Division of Research and Innovation Uttarakhand Dehradun India Adhiparasakthi College of Engineering Department of Electrical and Electronics Engineering Tamil Nadu Kalavai India

ISBN: (纸本)9798350396638

To improve communications network efficiency, situation identification is essential. the requirement for real-time scenario identification of vehicular communications is growing more pressing provided a certain vehicle movement makes vehicle interaction circumstances vibrant and that there are significant variations in signal propagation, vehicle speeds, and vehicular concentrations among possible situations. On the other hand, it has been demonstrated that cryptography methods are less effective at preventing insider attacks that originate inside the automotive communication network. A misbehaviour detection system has been found to be more effective in identifying and preventing insider attacks. this research study presents a misbehaviour detection system based on machine learning and is learned utilizing datasets produced by numerical simulations in a genuine vehicular distributed system. Vehicle communication systems may choose the proper spatial multiplexing and system integration by correctly detecting the current conditions in order to maintain an efficient and reliable operating condition. A back-propagation neural network (BPNN) is trained, and a scenario identification model is developed, using datasets that comprise channel properties acquired from channel measurements in various scenarios. Additionally, the proposed identification model's best performance-enabling model configuration technique is analysed and offered. the identification accuracy is then verified using validation information from the relevant circumstances. © 2023 IEEE.

关键词： Vehicles

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SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera Video Tracking and Recognition 8

SIVD: Dataset of Iranian Vehicles for Real-Time Multi-Camera...

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8th international Iranian conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Siahkali, Farbod Alavi, Seyed Amirmahdi Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Islamic Azad University Human and Robot Interaction Laboratory School of Computer Science Central Tehran Branch Tehran Iran

ISBN: (纸本)9781665476232

In this paper, a new publicly available 1 web-Scraped Iranian Vehicle Dataset (SIVD) for simultaneous real-time vehicle tracking and recognition is proposed. the datasets provided for Iranian cars in the literature have two fundamental problems. First, the lack of images from different angles, and second, the small number of classes compared to the dispersion of car models in the real world. therefore, for the purposes of this paper, Iranian vehicle images from car sales websites are collected, and the SIVD dataset is proposed which contains 29 classes and 36,705 images. this paper aims at developing a classification network for Iranian vehicle recognition and implement a real-time tracking system using the YOLOv5 network to perform real-time vehicle model recognition and tracking tasks simultaneously. the ResNet50 achieved an accuracy of 99.29%, the highest among the investigated classification networks.1https://***/Farbod-Siahkali/Iranian-Vehicle-Tracking-and-Recognition © 2022 IEEE.

关键词： Model automobiles

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10th international conference on Digital Arts, Media and Technology, DAMT 2025 and 8th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, NCON 2025

10th International Conference on Digital Arts, Media and Tec...

引用

10th international conference on Digital Arts, Media and Technology and 8th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications engineering, ECTI DAMT and NCON 2025

ISBN: (纸本)9798331543273

the proceedings contain 149 papers. the topics discussed include: the comparative study of artificial intelligence techniques: DeepMotion vs. Autodesk Maya in enhancing 3D animation creation and learning experiences;the design and development of media formats for public relations books and applications using augmented reality technology to promote tourism in Chiang Rai province;inspiring creativity: a comparative study of hands-on artifact interaction and 3D art viewing;a case study on customer knowledge management model to enhance social media marketing strategies of Chinese hotpot restaurant in Chiang Mai;multimedia learning theory for intelligent teaching software evaluation in Chinese language courses of thai primary schools;and the role of digital transformation and bank size in enhancing customer trust and banking performance.

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Design and Fabrication of Automatic hose cutting machine 8

Design and Fabrication of Automatic hose cutting machine

引用

8th international conference on Advanced Computing and Communication Systems, ICACCS 2022

作者： Arunkumar, P.M. Edwin, Lydia Kumar, G.Edwin Prem Athithya, N.K.Lalith Shibin thomas, S. Prawin Sankar, T.A. Sri Krishna College of Engineering and Technology Department of Mechatronics Engineering Tamil Nadu Coimbatore641008 India Sri Krishna College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore641008 India

ISBN: (纸本)9781665408165

Nowadays the need of automation in industry is immense for some time-consuming operations that increases the manpower and decreases the productivity, this study offers a solution to one of the time-consuming processes like hose cutting. the industry nowadays uses an old-fashioned cutting machine to cut the nylon hoses that needed to be cut in a precise manner. Our automatic hose cutting machine uses a stepper motor to cut the hoses for a precise length without manual interaction. Our project uses a shearing blade to cut down the hoses and roller to feed the hose into the shearing unit and these processes are controlled by PLC. thus, decreasing the cycle time of the cutting operation © 2022 IEEE.

关键词： Hose

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Emotion Recognition in Noisy Environments: Performance Analysis using Convolutional Neural Networks 8

Emotion Recognition in Noisy Environments: Performance Analy...

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8th international conference of Yearly Reports on Informatics, Mathematics, and engineering, ICYRIME 2023

作者： Borzì, Maria Grazia Beritelli, Ludovica Puglisi, Valerio Francesco Avanzato, Roberta Beritelli, Francesco Department of Electrical Electronic and Computer Engineering University of Catania Catania Italy Department of Computer Science University of Catania Catania Italy

Recognition of emotional state through the sound of the voice is a crucial element in human interactions. this process, known as emotional prosody, allows an individual’s emotions to be interpreted without the need to see his or her face or body language. the ability to identify emotions through voice is critical in areas such as psychology, health care, marketing and human-computer interaction technology. Moreover, in artificial intelligence systems and voice interfaces, the analysis of emotional prosody can improve the user experience and make interactions more personalized and intuitive. this study explores the robustness of a neural network in recognizing emotions within speech signals, considering the presence of environmental noise at different SNR levels. the study involves using public datasets containing different classes of emotions, training a CNN network to classify these emotional states, and then testing to evaluate the obtained performance. the results show that emotion recognition in speech is more accurate when the recording is clean and free of other noises. However, misclassification depends on the type of noise present and the type of emotion: indeed, it turns out that some emotions are more frequently misclassified than others. In fact, it is observed that accuracy is higher when using RAW data rather than MFCCs, with an accuracy of 75% compared to 60%. In addition, adding noise to the recordings results in a decrease in model performance. © 2023 Copyright for this paper by its authors.

关键词： Emotion Recognition

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Fifth international conference on computer Vision and Information Technology, CVIT 2024

Fifth International Conference on Computer Vision and Inform...

引用

5th international conference on computer Vision and Information Technology, CVIT 2024

ISBN: (纸本)9781510686755

the proceedings contain 10 papers. the topics discussed include: texture-attention discriminator for real-world image super-resolution;two-stage video scene segmentation method based on multimodal semantic interaction;design of material sorting system based on OpenMV;research on intelligent estimation of human posture in multiplayer complex scenarios;a video retrieval algorithm with embedded position coding for moment localization and highlight detection;a bio-inspired model for object motion direction and speed detection against colored backgrounds;analyzing handgun handling states: a deep learning approach using YOLOv8;using hash learning for a multi-model fashion recommendation system;and research on auditing of large-scale instruments and equipment opening and sharing in universities based on data mining.

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Attentive Task interaction Network for Multi-Task Learning 26

Attentive Task Interaction Network for Multi-Task Learning

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26th international conference on Pattern Recognition / 8th international Workshop on Image Mining - theory and Applications (IMTA)

作者： Sinodinos, Dimitrios Armanfard, Narges McGill Univ Mila Quebec AI Inst Dept Elect & Comp Engn Montreal PQ Canada

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Multitask learning (MTL) has recently gained a lot of popularity as a learning paradigm that can lead to improved per-task performance while also using fewer per-task model parameters compared to single task learning. One of the biggest challenges regarding MTL networks involves how to share features across tasks. To address this challenge, we propose the Attentive Task interaction Network (ATI-Net). ATI-Net employs knowledge distillation of the latent features for each task, then combines the feature maps to provide improved contextualized information to the decoder. this novel approach to introducing knowledge distillation into an attention based multitask network outperforms state of the art MTL baselines such as the standalone MTAN and PAD-Net, with roughly the same number of model parameters.

关键词： Knowledge engineering Measurement Learning systems Semantic segmentation Estimation Feature extraction Multitasking

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Applying YOLO Model in iCAR for Multi-Detection: Object Detection and Hand Gesture Recognition 5

Applying YOLO Model in iCAR for Multi-Detection: Object Dete...

引用

5th Technology Innovation Management and engineering Science international conference, TIMES-iCON 2024

作者： Setyaji, Rizko Trinanda Dikairono, Rudy Mujiono, Totok Departement of Electrical Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798350362602

computer vision technology is increasingly pivotal across various industries, particularly in transportation, where it plays a critical role in enhancing both efficiency and safety, especially in autonomous vehicles. this study addresses a significant challenge encountered by autonomous cars, exemplified by iCAR's inability to identify and provide access to traffic officers. the project's objective is to equip iCAR with the capability to recognize traffic officers and enable hand gesture-based access control. By leveraging Convolutional Neural Networks (CNNs) integrated with the You Only Look Once (YOLO V8) model, a robust model was developed and trained on a dataset comprising approximately 5000 images that include traffic officers and hand gestures. the study yielded promising results, as indicated by the F1 score analysis, with an average F1 score across all classes reaching 0.96, underscoring the model's effectiveness. through the integration of computer vision technology, iCAR facilitates seamless human-vehicle interaction by accurately discerning traffic officers and granting them access via hand gestures. ©2024 IEEE.

关键词： Convolutional neural networks

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the Influence of User Diversity on Motives and Barriers when Using Health Apps - A Conjoint Investigation of the Intention-Behavior Gap 1

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6th ifip TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 international Cross Domain conference on Machine Learning and Knowledge Extraction (CD-MAKE)

作者： Roessler, Eva Halbach, Patrick Burbach, Laura Ziefle, Martina Valdez, Andre Calero Rhein Westfal TH Aachen Human Comp Interact Ctr Campus Blvd 57 D-52076 Aachen Germany Univ Lubeck Inst Multimedia & Interact Syst Ratzeburger Allee 160 D-23562 Lubeck Germany

ISBN: (数字)9783031144639

ISBN: (纸本)9783031144639;9783031144622

Currently, there is a major health problem in our society, which partially is the result of an insufficient level of physical activity. Despite existing intentions, people sometimes fail to turn them into action and engage in physical activity. this intention-behavior gap provides a framework for the topic under study. Fitness apps offer a way to assist and support people in implementing physical activity in their daily routine. therefore, this paper investigates the influence of user diversity on motives and barriers to fitness app use. For this purpose, a choice-based conjoint study was conducted in which 186 subjects were asked to repeatedly choose their favorite between three fictitious constellations of fitness apps. the apps were configured based on selected attributes. Differences in decision-making between men and women, exercisers and non-exercisers, as well as influences of certain personality dimensions and motivational types have been found. the results provide important clues that may help to customize fitness apps to specific user groups and for further research.

关键词： Fitness apps Health apps Privacy Group recommendation User modelling human-computer interaction

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Survey on Mentor Monitoring System 8th

Survey on Mentor Monitoring System

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8th international conference on Information and Communication Technology for Intelligent Systems, ICTIS 2024

作者： Makanyadevi, K. Ragavi, M. Sanjay, M. Hariharan, G. Department of Computer Science and Engineering M.Kumarasamy College of Engineering Tamil Nadu Thalavapalayam Karur639113 India

ISBN: (纸本)9789819766833

Currently, by the mentor monitoring the gaps in several areas of constraint between mentors and students are bridged. For mentors and students alike, this system offers an online mentoring system. In traditional systems, there is a big communication gap between mentors and students. the traditional setup requires that the mentor and students be present in the same physical area. It has a protracted documentation process, is time-consuming, and doesn’t allow for much interaction. To solve all these issues, we are creating a mobile application that will provide mentors and students access to the information management they need. Students are paired with mentors based on their areas of interest, and mentors may aid students with both their academic and personal growth. Students and mentors can contact via internet chat, and all data is handled digitally. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Students

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