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检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18818 条记录，以下是411-420 订阅

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Research on the function test of the porous media system in tunnel construction based on virtual computer simulation mathematical model 3

Research on the function test of the porous media system in ...

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3rd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Hao, Huijuan Henan Technical College of Construction Zhengzhou450064 China

ISBN: (纸本)9798350398410

The application of computer image virtual reality technology in civil engineering has very obvious practicability. In this paper, one of the AutoCAD 3D models of virtual simulation is built with the help of a computer system, and a fast conversion process is generated. At the same time, a computer program is developed in this paper. The mathematical model of surface subsidence of porous media in civil engineering tunnel construction is constructed based on the fractional differential equation medium theory. Through this model's data analysis and model research, the application functions of tunnel construction crack control simulation, visual query, and comprehensive analysis are realized and verified. © 2023 IEEE.

关键词： Porous materials

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Efficient net-based deep learning: A deep-fake image detection 3

Efficient net-based deep learning: A deep-fake image detecti...

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3rd international conference on Communication, control, and Intelligent Systems, CCIS 2024

作者： Singh, Rohan Sharma, Dilip Kumar Kumar Jain, Praphula Gla University Department of Computer Science and Engineering Mathura India Gla University Department of Computer Engineering and Application Mathura India Mits Gwalior Department of Computer Science and Engineering MP India

ISBN: (纸本)9798331528201

With the substantial volume of social media data generated daily and the concurrent emergence of powerful multimedia modification techniques, detecting manipulations in photographs and videos has become an important task. This study examines the strength of a deep learning-based efficient net model for detecting manipulation in multimedia images. This study examines the publicly accessible benchmark dataset DFDC to prove its efficiency. We also highlighted the real-world challenges and emerging trends to combat deep-fakes. The research experiment resulted in and confirmed the efficiency of Efficient-Net as it performed well in both the training and testing stages, exhibiting more accuracy and reduced loss. The test accuracy varies between 50 and 95, with epochs spanning from 0 to 10. © 2024 IEEE.

关键词： Deep Learning Deepfakes Efficient Net Fake Image Video

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Violence Prediction System Using Bi-LSTM 3

Violence Prediction System Using Bi-LSTM

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Sai Kiran, P. Tirapathi Reddy, B. Keerthi, Goudu Vimal Avanigadda, Venkata Subbarao Vinnakota, Chandrika Priyanka Sri, Deekollu Aruna Prasad v Potluri Siddhartha Institute of Technology Department of Computer Science and Engineering Vijayawada India Prasad v Potluri Siddhartha Institute of Technology Department of Information Technology Vijayawada India Prasad V. Potluri Siddhartha Institute of Technology Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350322842

Usage of video surveillance to monitor public places has been rapidly increasing. Traditionally, people use human labor to monitor the provinces. To decrease human intervention, one can use computer vision and machine learning techniques for safety monitoring. Generally, the intensity of an action involving violence can be measured from the accuracy of the system used. This work implements an architecture for classifying a video into violent or non-violent, and identifying the violent scenes using MobileNet V2 and bi-directional LSTM. A dataset of 2000 videos are used to train the model, combining hockey fights, movie fights, and real-time fights. The model achieved an accuracy of up to 95%. © 2023 IEEE.

关键词： Long short-term memory

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Design of a Hybrid Energy Harvesting System Using Exercycle with IoT Monitoring 3

Design of a Hybrid Energy Harvesting System Using Exercycle ...

引用

3rd IEEE international conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2024

作者： Jimiera, Theodor Jeb R. Chavez, Chito Anton C. Ang, Gerard School of Electrical Electronics and Computer Engineering Mapua University Manila Philippines

ISBN: (纸本)9798350387193

This study explores, design and implementation of a hybrid energy harvesting system utilizing piezoelectric transducers and electromagnetic induction in exercycles, converting mechanical energy to electricity. The prototype incorporates electromagnetic coils, magnets, piezoelectric disc transducers, a charging circuit module, a battery, and an Arduino for monitoring. Performance assessments involved collecting data on voltage, current, power, and efficiency in controlled conditions during test trials. ANOVA tests were employed for data analysis. Three controlled setups were executed: Piezoelectric Before Non-Inverting Summing Amplifier, Electromagnetic Induction Before Non-Inverting Summing Amplifier, and After Non-Inverting Summing Amplifier. During 15-minute exercise sessions, the device consistently generated an average of 4.5 V in the Electromagnetic setup and 2.19 V in the Piezoelectric setup. The hybrid setup, after the summing amplifier, produced an average of 6.69 V. The battery's initial voltage was 4V, reaching a final voltage of 4.43V, indicating a state-of-charge increase from 78% to 86% after all trials. © 2024 IEEE.

关键词： Hybrid power

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Research on image restoration of objects passing through ground glass 3

Research on image restoration of objects passing through gro...

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3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Li, Yufeng Tian, Erming Li, Qin Han, Huiyan Institute for Civ-Mil Integration & Collaborative Innovation North University of China Taiyuan China North Automatic Control Technology Institute Foreign Trade R&d Department Taiyuan China North University of China Data Science and Technology Taiyuan China

ISBN: (纸本)9781665459112

In this paper, the image restoration mechanism of objects through ground glass is studied by digital holography. The holographic scattering imaging system is designed and built, the mathematical model of ground glass is established, and an algorithm to eliminate the speckle noise of ground glass is proposed. The digital hologram obtained from the experiment is reconstructed by Fresnel reconstruction algorithm. The experimental results verify the correctness of the theoretical algorithm and experimental method, and it has important reference value for in-depth study of image restoration of objects passing through complex media in the future. © 2022 IEEE.

关键词： Image reconstruction

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Deep CNN-Based-Flower Species Recognition System 3

Deep CNN-Based-Flower Species Recognition System

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3rd international Scientific conference of Engineering Sciences, ISCES 2023

作者： Albawi, Saad Waleed, Jumana Abboud, Ali J. College of Engineering University of Diyala Department of Computer Engineering Diyala Iraq College of Science University of Diyala Department of Computer Science Diyala Iraq

ISBN: (纸本)9798350302912

There are numerous species of flowers worldwide, and these species hold outstanding economic, cultural, and ecological significance in human life. Flower species recognition benefits applications like searching for flowers in digital libraries and floriculture. Recently, with the high advancement in computer vision and deep learning technologies, automated flower species recognition systems have attracted many scientific researchers. Exploiting deep learning to recognize flower species from images accurately represents an existing problem that should be resolved. Therefore, this paper uses various deep convolutional neural network (CNN) approaches like (VGG-19, ResNet-152V2, MobileNet-V2, InceptionResNet-V2, DenseNet-201, and Xception) are carried out to recognize various flower species. The flower images dataset acquired from Kaggle includes five categories and is utilized in the experiments. Among other implemented approaches, DenseNet201 attained the highest results with an accuracy of 94.12%. © 2023 IEEE.

关键词： Digital libraries

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3rd international Scientific and Practical conference on Digital and Information Technologies in Economics and Management, DITEM 2023

3rd International Scientific and Practical Conference on Dig...

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3rd international Scientific and Practical conference on Digital and Information Technologies in Economics and Management, DITEM 2023

ISBN: (纸本)9783031553486

The proceedings contain 20 papers. The special focus in this conference is on Digital and Information Technologies in Economics and Management. The topics include: Intra System Links Dynamics as a Cause of Development Cyclicity: The Simplest Equations;improving the Sustainability and Safety of the City Transport System Through the Application of computer Modeling;development of Software for the Analysis of Socio-Economic Indicators Based on Neural Networks;estimation of the Cost of Developing a Digital Twin Using Virtual Reality Technologies in the Metallurgical Industry;formation of Artificial Collective Intelligence Based on the Theory of Active Systems;nonlinear Modeling of the Population State of Gregarious Locusts;designing the Architecture of a Multi-agent City Management System Using Advanced Object-Oriented Modeling;analysis of the Impact of Fintech on the Economy: Japan and Russia Case;simulation of a Tubular Pyrolysis Reactor Using Comsol Multiphysics Software;an Overview on Data Augmentation for Machine Learning;keyboard Handwriting as a Factor of User Authentication;development of an Algorithm for Constructing Complex Fractal Images Using the L-Systems Method for Textile and Building Materials Production Enterprises;predicting the Popularity of Social Network Publications Based on Content Analysis Using the Transformer Language Model;Classification of Building Components Using Artificial Intelligence Based on Meta-Information in BIM Models;computer vision System for Monitoring User Attention in Interactive User Interfaces;processing of Data on Power Consumption in the Management of Energy Resources of the Regional Electrical Complex;development of a Probabilistic Model for Predicting Advertising Conversion Using Recurrent Neural Networks.

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A Real-Time Multimodal Deep Learning for Image-to-Cartoon Conversion 3

A Real-Time Multimodal Deep Learning for Image-to-Cartoon Co...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Karthik, Raja Pavan Vamsi, Kalla Yadu Reddy, Veeramreddy Sourya Tejarsha Abhishek, S. Anjali, T. Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India Rolls-Royce Inc Bangalore India

ISBN: (纸本)9798350343632

In the era of digital imagery, there is a great interest in finding new and creative ways to express ourselves and make our images look beautiful. One such fascinating method is cartoonization, a process that transforms ordinary images into visually appealing cartoon images. This paper explores the integration of cutting-edge computer vision algorithms, traditional image processing methods, and Neural Networks to achieve cartoonization. The main focus is on combining object segmentation with cartoonization in a smooth and seamless way, which offers a unique and innovative approach to improving images. By thoroughly considering various techniques and how they can be used together, our research not only gives a complete understanding of these methods but also highlights how they can transform the field of digital artistry. By exploring the integration between methods, the study sheds light on how these techniques contribute to the evolving landscape of digital artistry. The research suggests that the fusion of computer vision, traditional image processing, and Machine Learning techniques holds promising potential for pushing the boundaries of creative expression in the digital realm, offering new ways for creating efficient cartoon images. © 2023 IEEE.

关键词： Cartoonification Cartooning Color Quantization Edge Detection Region-Based Convolutional Neural Networks (R-CNN)

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A Unified control for a Soft-Switched Dual Active Bridge DC-DC Converter 3

A Unified Control for a Soft-Switched Dual Active Bridge DC-...

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3rd IEEE international conference on control, Instrumentation, Energy and Communication, CIEC 2024

作者： Chakraborty, Souptik Paul, Dhrubojyoti Chowdhuri, Sumana Saha, Shib Sankar University of Calcutta Dept. of Applied Physics W.B Kolkata700006 India Kalyani Govt. Engineering College Dept. of Electrical Engineering W.B Nadia Kalyani India Electrical Engineering Kalyani Government Engineering College Kalyani India

ISBN: (纸本)9798350313703

The Dual Active Bridge (DAB) is an isolated converter topology that uses a transformer to offer step-up/step-down capability as well as galvanic isolation for the converter. This DAB Converter has intrinsically zero voltage switching (ZVS) capability, but in a very limited power range, if operated in traditional control mode. The ZVS range of different control techniques namely Phase-shift modulation (PSM), single pulse-width modulation (SPWM), and dual pulse-width modulation (DPWM) control modes for different power ranges have been estimated in this paper in an updated and simpler manner. Three different variables: the phase shift between the primary and secondary transformer voltages, the primary voltage width, and the secondary voltage width are used here to manipulate these control schemes. A hardware prototype of a 600W DAB converter using Silicon MOSFET has been designed and developed to operate at 100 kHz switching frequency amalgamating with three control strategies as mentioned above. The performance of the DAB converter has been initially estimated through mathematical analysis and computer simulations in MATLAB Simulink. © 2024 IEEE.

关键词： Zero voltage switching

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Voiced Subordinate for Visually Impaired in record maintenance with Proximal Object Recognition and Voice Assistant Framework 3

Voiced Subordinate for Visually Impaired in record maintenan...

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3rd international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2023

作者： Sajini, S. Pushpa, B. Annamalai University Faculty of Science Department of Computer and Information Science Tamil Nadu Chidambaram India

ISBN: (纸本)9781665494007

Proximal Object detection using computer vision is one of the important domains that comprehends the users or objects in front of them through vision Glasses to recognise objects and inform the Visually Impaired (VI). The major objective of the research was to design a Proximal Object Recognition and Voice Assistant Framework (PORVAF) that detects the object with plots and recognises the objects using the COCO dataset that shares global database for recognising objects. The recognised objects were further tested for proximity and analysed for the percentage of accuracy of detecting the object using computer vision Techniques. Along with the percentage, the date and time of the recognition of objects were recorded and stored in the local database and sent as voice output for the visually impaired user. This framework outperformed the benchmark models by achieving high accuracy of proximality object detection. The significance of the work is to assist the VI in office record maintenance and to remove unemployability for VI people in the world. © 2023 IEEE.

关键词： Object recognition

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