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

共 19046 条记录，以下是4031-4040 订阅

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Sliding Mode control of Permanent Magnet Synchronous Motor Based on Disturbance Observer 3

Sliding Mode Control of Permanent Magnet Synchronous Motor B...

引用

2021 3rd international conference on computer, Communications and Mechatronics Engineering, CCME 2021

作者： Song, Zehang Sha, Linlin Yao, Xiaodong School of Electrical Engineering Shanghai DianJi University Shanghai201306 China Minge New-Type Motor and Electronic Control Research Institute Guangdong Province Foshan528599 China

A sliding mode control method of surface mount permannent magnet synchronous motor (SPMSM) based on disturbance observer was proposed to solve the problem of internal parameter disturbance caused by temperature change during PMSM operation. Firstly, a disturbance observer based on parametric disturbance is established. Secondly, a new double power approach law is used to design the speed ring controller, and the stability of the controller and observer is proved by Lyapunov stability theory. The results turns out that the new method can clearly improve the performance of the motor, weaken chattering, enhance the robustness and anti-interference ability. © Published under licence by IOP Publishing Ltd.

关键词： Sliding mode control

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Real-Time Defogging using Dark Channel Prior for Enhanced Visibility

Real-Time Defogging using Dark Channel Prior for Enhanced Vi...

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Emerging Trends in Electrical, control, and Telecommunication Engineering (ETECTE), international conference on

作者： Zohaib Mushtaq Obaid Ur Rehman Usman Ali Muhammad A. Latif Dept. of Electrical Electronics and Computer systems University of Sargodha Sargodha Pakistan Dept. of Computer and Information System Cleveland State University OH USA

ISBN: (数字)9798331504861

ISBN: (纸本)9798331504878

The presence of fog is a notable obstacle for capturing images, particularly in the early morning hours. The diminished sight impedes the capacity to get distinct and comprehensive information from the surroundings. In order to tackle this issue, a rapid and live vision-based dehazing method is suggested. The objective of the technology is to dissipate the fog and enhance visual acuity. It does this by implementing four steps: using an exponential moving average filter to diminish the impact of noise and enhance clarity, preprocessing the filtered frames, detecting fog with the Gaussian blur technique, and applying the dark channel prior approach to achieve optimum contrast and remove fog. Comprehensive testing were carried out on live recordings to showcase the system's ability to significantly improve sight in different foggy situations. This technique demonstrates the superior performance in terms of following parameters like, an accuracy, precision, recall, and F1 score compared to previous investigations. Our methodology achieved the greatest accuracy when compared to state-of-the-art transfer learning convolutional neural networks.

关键词： Visualization Accuracy Transfer learning Noise Streaming media Information filters Real-time systems Recording Remote sensing Testing

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Automatic recognition of GPR localized targets images using C3 algorithm

Automatic recognition of GPR localized targets images using ...

引用

Sciences and Techniques of Automatic control and computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Abdussalam Masaud Ammar Amira Youssef Ellafi Said Elkhatalli Faculty of Electronic Technology Tripoli Libya Faculty of Electronic Technology BaniWalid Libya

A near-surface geophysical technique with several uses is ground penetrating radar, often known as GPR, ground probing radar, or georadar. GPR has been utilized effectively over the past 30 years to aid with limiting issues in various domains, including environmental site characterization, archaeology, glaciology, etc. The electromagnetic signal produced by the GPR, a Non Destructive Testing (NDT) method, penetrates the subsurface and measures the amplitude and duration of the signal that is reflected back. GPR data may be used to create high-resolution cross-sections of the scanned material. After pre-processing the input GPR images, a special thresholding approach is employed to separate the regions of interest from background. The next step is to utilize a column connection clustering (C3) approach to divide the areas of interest from one another.

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Detection of Breast Tumor Using Microstrip Ring Resonator

Detection of Breast Tumor Using Microstrip Ring Resonator

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Sciences and Techniques of Automatic control and computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Safaa Kaled Jurnaz Bashir Moh. Khamoudi Dept. of Electrical and Computer Eng. Libyan Academy Tripoli Libya Electronic Research Center Applied Research and Development Org. Tripoli Libya

In this paper a new method will be used to detect breast cancer without affecting the human body. This will use a microstrip ring resonator operated at 2.4 GHz with supporting material for detecting of tumor based on measuring the resonance frequency, effective dielectric constant and then calculated dielectric *** breast phantom was designed and simulated in the form of a rectangle shape containing, Skin, Fat and Glandular, whereas the tumor is shaped as spherical with different *** results was carried out using CST software, were the tumor was detected by resonance frequency and return loss by comparing between the healthy and affected breast. The results showed that, the tumor with size of 0.5mm radius was ***, this method was simplified by removing the support material and the simulation process is repeated again and it gave a close simulated results as with it.

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Dynamic Object Tracking Based on Triplet Relationship Guided Sampling Consensus Algorithm 3

Dynamic Object Tracking Based on Triplet Relationship Guided...

引用

2023 3rd international conference on computer, Remote Sensing and Aerospace, CRSA 2023

作者： Zhou, Jiaxing Yao, Youxin Chen, Xiang Guo, Hanlin Huang, Qixuan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361000 China Shanghai Satellite Engineering Institute Shanghai201109 China

Compared with the traditional methods based on the prediction of moving object trajectory, the method based on image registration has the advantage of not relying on the object motion equation to track the object. However, in the case of a large number of outliers, the image matching method has the defects of inadequate filtering of outliers or erroneous filtering of incomers due to the limitations of spatial constraints of feature matching pairs, which will make the tracking of flying objects inaccurate or impossible. During the flight, the object may be in a similar background and the image shooting angle is different, which makes the object imaging angle change, resulting in a large number of outlier interference. Because of the above situation, this paper adopted an improved TRESAC algorithm based on RANSAC, which used a feature matching method based on a triplet relationship to effectively filter outliers and then adopted an initial data subset selection strategy to increase its robustness. Experimental results show that the TRESAC algorithm can filter outliers quickly and accurately, and the object is still tracked effectively under the condition of similar background and pose change. © Published under licence by IOP Publishing Ltd.

关键词： Statistics

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Robotic Manipulators: A control Architecture Approach Based on Deep Reinforcement Learning and Simulation Environments

Robotic Manipulators: A Control Architecture Approach Based ...

引用

Electrical, computer, Communications and Mechatronics Engineering (ICECCME), international conference on

作者： Carlos Calderon-Cordova Roger Sarango Dept. of Computer Science and Electronics Universidad Tecnica Particular de Loja Loja Ecuador

With the rapid technological advancement and the increasing need for more intelligent robotic systems in various work areas, it is essential that such systems exhibit improved robustness and control characteristics. In this context, Deep Reinforcement Learning has become a key technique for developing more accurate and efficient control models in robotics. Deep Reinforcement Learning involves training models from a simulated environment that allow different scenarios to be explored without the limitations and constraints of the real world. This allows robotics engineers and developers to fine-tune and improve the control systems of robotic manipulators, making them more reliable and effective in their work. In this article, we present an overview of the main tools, algorithms and simulators used for end-to-end control of robotic manipulators. The use of simulators and Deep Reinforcement Learning techniques in robotic manipulator training allows developers to train robots safely and effectively, without having to deal with the costs and risks associated with training robots in real environments. In addition, concrete examples and applications are included that illustrate how these techniques can be applied to improve the performance and efficiency of robotic manipulator control.

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A Role of Wearable Health Technology in Smart Cities 3rd

A Role of Wearable Health Technology in Smart Cities

引用

3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Chauhan, Ritu Kaur, Harleen Mehta, Khushi Alankar, Bhavya Artificial Intelligence and IoT Lab Center for Computational Biology and Bioinformatics Amity University Uttar Pradesh Noida India Department of Computer Science and Engineering School of Engineering Sciences and Technology Jamia Hamdard New Delhi India Amity Institute of Biotechnology Amity University Uttar Pradesh Noida India

ISBN: (纸本)9789819719426

In this rapidly changing era of the world, healthcare devices are revolutionizing, which enables the continuous measurement of crucial biological markers for diagnostic purposes, physiological health monitoring, and evaluation. Hence, wearable devices have transformed into accessories, embedded clothing, body adaptors, and body implants. Additionally, the emergence of wearable healthcare devices that facilitates the diagnosis and prognosis by using tiny sensing devices and biomedical devices has greatly enhanced the efficiency as well as the quality of medical care facilities results in the tremendous advancements in semiconductor technology, biomedical technologies, and nano-sized materials over the past few decades. Meanwhile, the devices could provide real-time feedback, allowing users to analyze their health and monitor in a specific period that has been assigned to the smart wearable devices, even though the industries and manufacturers are intensely interested in interpreting the factors that influence the adoption of new smart technologies, which helps to improve the performance and viability of wearable devices to fascinate consumers. Hence, the advancements in technology are regarded as trustworthy equipment for everlasting monitoring of health that are frequently used to monitor and control a diverse of health tracking predictors in the surroundings, including monitoring health and wellness of the body. In recent years, it has been focused on the study of a wide range of parameters closer to advancements in smart technology. As a result, these smart devices are now utilized in a variety of healthcare monitoring applications, one of the most crucial aspects of data collection is the various factors based on bodily activities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

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Convolutional Neural Networks for Enhanced Real-Time Traffic Incident Detection and Image Classification 3

Convolutional Neural Networks for Enhanced Real-Time Traffic...

引用

3rd international conference on Advancement in Computation and computer Technologies, InCACCT 2025

作者： Monisha, J. Ramalingam, L. Mathankumar, S. Narayanasamy, P. Rajmohan, M. Murugan, S. R.M.K. College of Engineering and Technology Tamil Nadu Chennai India Department of Artificial Intelligence and Data Science Loyola Institute of Technology Tamil Nadu Chennai India Tamil Nadu Salem India Department of Mathematics Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Tamil Nadu Chennai India Department of Electronics and Communication Engineering Hindustan Institute of Technology and Science Tamil Nadu Chennai India Department of Biomedical Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798331543891

Traffic incident detection and classification are essential aspects of enhancing road safety and efficiency. A new approach to enhancing real-time traffic incident detection and image classification with the help of Convolutional Neural Networks (CNNs), viz., Alex Net, is presented in this paper. Alex Net, a deep CNN architecture that is widely used for image recognition, is employed to classify traffic images and videos for incident identification. The system makes use of the ability of the model to learn robust features to identify images as different events, such as accidents, roadblocks, and vehicle breakdowns. Low latency and high accuracy incident identification is done by the system utilizing real-time traffic camera data and Alex Net. Differentiation between different types of events. This is for the sake of enhancing reaction time, enabling effective traffic management, and differentiating between events. AlexNet enables 92% accuracy in real-time traffic detection and image classification, enhancing the efficiency of intelligent transportation systems. The results demonstrate how deep learning (DL) methods can revolutionise traffic monitoring systems and improve safety protocols for drivers. © 2025 IEEE.

关键词： Highway traffic control

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Using ECLAT Algorithm for Privacy Preserving on Publishing Data

Using ECLAT Algorithm for Privacy Preserving on Publishing D...

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Sciences and Techniques of Automatic control and computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Osama M Ben Omran Department of Computer Science Faculty of Information Technology University of Benghazi Benghazi Libya

many organizations such as online organizations, hospitals, and universities use massive amounts of customer information and use Database systems to enter their data. Many services and benefits are provided by these organizations to the public. The organizations want to publish the data and information for the purpose of research and analysis to obtain many benefits and advantages to improve their work. On the other hand, the data include individuals' sensitive and private information, therefore, organizations are concerned about the security as well privacy; in fact privacy is an important issue when organizations publish their data. This paper suggests a technique to preserve the privacy of the information. The proposed technique uses the ECLAT algorithm which is efficiently mined using the vertical data format. In addition to the ECLAT algorithm, the proposed technique uses some extra steps to process and manage data and to be prepared and secure for publishing.

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Reconstructing the Medical Image by Autoencoder with Stochastic Processing in Neural Network 3

Reconstructing the Medical Image by Autoencoder with Stochas...

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3rd international conference on Inventive Research in Computing Applications, ICIRCA 2021

作者： Senthil Kumar, V. Jayalakshmi, V. Vels Institute of Science Technology and Advanced Studies Department of Computer Science Chennai India Vels Institute of Science Technology and Advanced Studies Department of Computer Applications Chennai India

ISBN: (纸本)9780738146270

The working on image to perform different operation is known as image processing. Digital Image is a collection of a defined number of pixels. Each feature has a particular pixel value at a specific position. Image restoration can be considered as an image enrichment where the final image is printed with more important features that create more appealing for the spectator but it is not essential to create genuine data from the point of a scientific vision. Autoencoder is one of the techniques in artificial neural network to analyze and predict a huge volume of data with different many features. This technique has three stages namely the first one is encoding, second one is compression and third one is decoding. Denoising autoencoder is an enhanced technique for image processing to reconstruct the damaged image to original image. Denoising autoencoder techniques are applying on the medical image to get the high quality image in digital image processing. In this paper, stochastic gradient descent algorithm is applied to predict the damaged pixel and replaced by new pixel values. The result is better than previous result in medical images. © 2021 IEEE.

关键词： Restoration

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