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

共 18817 条记录，以下是4511-4520 订阅

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Analysis of COVID-19 Based on SEQR Dynamic Model in Xiaogan City, Hubei Province 3

Analysis of COVID-19 Based on SEQR Dynamic Model in Xiaogan ...

引用

3rd international conference on Modeling, Simulation, Optimization and Algorithm, ICMSOA 2021

作者： Shen, Jiayu Zhang, Jiehao Wen, Yongxian College of Computer and Information Fujian Agriculture and Forestry University Fuzhou China Institute of Applied Statistics Fujian Agriculture and Forestry University Fuzhou China

In this study, we established a SEQR model for the spread of COVID-19. The impact of city lockdown measures and other factors on the spread of the epidemic was discussed in this paper through dynamic analysis and numerical simulation of the model. The research results showed that the input ratio of the exposed population should be controlled to at least 0.001 if the government wanted to effectively control the epidemic. Closing the city was the most effective way. The exposed population of COVID-19 in Xiaogan City was hoping to be cleared on February 29 under strict control. The closed city could be released around March 28. But at the same time, we should pay attention to prevent the virus from entering it again. The peak number of existing patients would reduce by about 1,400 if city lockdown measures were taken in Xiaogan City four days in advance. © Published under licence by IOP Publishing Ltd.

关键词： COVID-19

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Design of Intelligent Car control Based on EEG Signal 3

Design of Intelligent Car Control Based on EEG Signal

引用

2022 3rd international conference on Internet of Things, Artificial Intelligence and Mechanical Automation, IoTAIMA 2022

作者： Tang, Lili College of Computer and Information Engineering Zhixing College of Hubei University Wuhan430011 China

Based on the TGAM (ThinkGear Asic Module) EEG sensor, this paper mainly carried out the research and design of intelligent car control method. By collecting brainwave and analyzing TGAM output data, the required concentration parameters can be obtained. STM32F1 series MCU is used as the main controller to analyze data and control the car. The bluetooth module based on Bluetooth 4.0 technology is used to realize data communication. The power system includes L298N motor drive module, two independent DC motor and universal wheel. The software part mainly uses C language for development, the core part of the program is ThinkGear communication protocol analysis. Finally, the design realizes the control of the vehicle motion state through different values of concentration, which lays a foundation for further popularization and application. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： DC motors

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Low Resolution Deepfake Face Detection using Multi-Scale Discrete Cosine Transform and vision Transformer

Low Resolution Deepfake Face Detection using Multi-Scale Dis...

引用

international Symposium on Advanced Computing and Communication (ISACC)

作者： Main Uddin Zhangjie Fu Xiang Zhang Abu Bakor Hayat Arnob School of Computer Science Nanjing University of Information Science and Technology Nanjing China School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing China

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Deepfake technology uses generative adversarial networks to produce highly authentic counterfeit images and videos, which raises a significant global security concern by disseminating fake information through online platforms, especially on social media. Researchers have developed sophisticated models for deepfake detection, demonstrating high performance on high-resolution images. However, their effectiveness significantly diminishes when applied to low-resolution images. We propose a simple framework that utilizes multi-scale discrete cosine transform and vision transformer for low-resolution deepfake face detection. This framework introduces a multi-scale frequency filter fusion approach to extract subtle frequency features in the frequency domain. Our proposed network has been tested on the FaceForensics++ and Celeb-DF datasets, and it outperforms existing models, achieving superior AUC and F1 scores.

关键词： Deepfakes Image resolution Social networking (online) Frequency-domain analysis Transformers Feature extraction Discrete cosine transforms Face detection Security Intelligent systems

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rdMMLND: A New Robust Deep Model for Multiple License Plate Number Detection in Video 3rd

RDMMLND: A New Robust Deep Model for Multiple License Plate ...

引用

3rd international conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2022

作者： Kumar, Amish Shivakumara, Palaiahnakote Pal, Umapada Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9783031090363

Accurate multiple license plate detection without affecting speed, occlusion, low contrast and resolution, uneven illumination effect and poor quality is an open challenge. This study presents a new Robust Deep Model for Multiple License Plate Number Detection (rdMMLND). To cope with the above-mentioned challenges, the proposed work explores YOLOv5 for detecting vehicles irrespective of type to reduce background complexity in the images. For detected vehicle regions, we propose a new combination of Wavelet Decomposition and Phase Congruency Model (WD-PCM), which enhances the license plate number region such that the license plate number detection step fixes correct bounding boxes for each vehicle of the input images. The proposed model is tested on our own dataset containing video images and standard dataset of license plate number detection to show that the proposed model is useful and effective for multiple license plate number detection. Furthermore, the proposed method is tested on natural scene text datasets to show that the proposed method can be extended to address the challenges of natural scene text detection. © 2022, Springer Nature Switzerland AG.

关键词： Wavelet decomposition

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Dynamic access control technology based on zero-trust light verification network model 3

Dynamic access control technology based on zero-trust light ...

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3rd IEEE international conference on Communications, Information System and computer Engineering, CISCE 2021

作者： Zhang, Pengfeng Tian, Chuan Shang, Tao Liu, Lin Li, Lei Wang, Wenting Zhao, Yiming State Grid Zibo Power Supply Company Zibo China State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Research Institute Jinan China School of Computer Science and Technology Harbin Institute of Technology at Weihai Weihai China

ISBN: (纸本)9780738112152

With the rise of the cloud computing and services, the network environments tend to be more complex and enormous. Security control becomes more and more hard due to the frequent and various access and requests. There are a few techniques to solve the problem which developed separately in the recent years. Network Micro-Segmentation provides the system the ability to keep different parts separated. Zero Trust Model ensures the network is access to trusted users and business by applying the policy that verify and authenticate everything. With the combination of Segmentation and Zero Trust Model, a system will obtain the ability to control the access to organizations' or industrial valuable assets. To implement the cooperation, the paper designs a strategy named light verification to help the process to be painless for the cost of inspection. The strategy was found to be effective from the perspective of the technical management, security and usability. © 2021 IEEE.

关键词： Trusted computing

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Detection of Life-threatening Malignant Cardiac Arrhythmias Using Machine Learning Methods

Detection of Life-threatening Malignant Cardiac Arrhythmias ...

引用

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

作者： Mariam Krkara Alla Zwawi Mohamed Samir Elbuni Department of Computer Engineering University of Tripoli Tripoli Libya

Malignant cardiac arrhythmias such as ventricular tachycardia (VT) and ventricular fibrillation (VF) cause Cardiac arrest (CA) or Sudden cardiac death (SCD); which accounts for 50% of all cardiac deaths. In this study, we proposed a patient-general system that analyzes and detects VT/VF arrhythmic episodes in ECG signals by classifying instances as either normal or arrhythmic. A great deal of experimental work was conducted to choose the best algorithms for preprocessing, the extraction of a comprehensive set of time-and frequency-domain features from a specific window length of the ECG signals to capture information about their amplitude, frequency, and morphology, and for feature selection, and classification. Three different window sizes were tested 10s, 20s, and 60s. On testing data with 10 s-window-size, the Random Forest and kNN ensembles obtained the best results with an accuracy (acc) of 99.11%, a sensitivity (se) of 98%, and a specificity (sp) of 99.6%. We also show through comparative results that the Minimum Redundancy Maximum Relevance (mRMR) feature selection algorithm outperforms the Principal Component Analysis (PCA) algorithm in choosing the optimal feature combinations. Our results demonstrate the potential of an automated, accurate, and robust detection system and how it could contribute significantly to the enhancement of the diagnostic process of arrhythmias and the prediction/prevention of cardiac arrest.

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Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs 18

Graph-to-3D: End-to-End Generation and Manipulation of 3D Sc...

引用

18th IEEE/CVF international conference on computer vision (ICCV)

作者： Dhamo, Helisa Manhardt, Fabian Navab, Nassir Tombari, Federico Tech Univ Munich Munich Germany Google Mountain View CA 94043 USA

ISBN: (纸本)9781665428125

controllable scene synthesis consists of generating 3D information that satisfy underlying specifications. Thereby, these specifications should be abstract, i.e. allowing easy user interaction, whilst providing enough interface for detailed control. Scene graphs are representations of a scene, composed of objects (nodes) and inter-object relationships (edges), proven to be particularly suited for this task, as they allow for semantic control on the generated content. Previous works tackling this task often rely on synthetic data, and retrieve object meshes, which naturally limits the generation capabilities. To circumvent this issue, we instead propose the first work that directly generates shapes from a scene graph in an end-to-end manner. In addition, we show that the same model supports scene modification, using the respective scene graph as interface. Leveraging Graph Convolutional Networks (GCN) we train a variational Auto-Encoder on top of the object and edge categories, as well as 3D shapes and scene layouts, allowing latter sampling of new scenes and shapes.

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IoT Based Voice controlled Autonomous Robotic Vehicle Through Google Assistant 3

IoT Based Voice Controlled Autonomous Robotic Vehicle Throug...

引用

3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Gupta, Meenu Kumar, Rakesh Chaudhary, Raju Kumar Kumari, Jayshree Chandigarh University Department of Computer Science and Engineering India

ISBN: (纸本)9781665438117

Internet of Things (IOT) which aims to describe the execution of a voice-controlled automated vehicle utilizing Arduino IDE. The thought is to at first arrangement the Equipment of the Robot Car and a while later code the entire working using our previous data on programming. The code will by then be reenacted on programming (IDE) and later be interfaced with the gear. The client provides explicit voice orders to the mechanical vehicle through google right hand present on the cell phone. At the receiving side data will be received through Thing Speak (cloud computing) to the ESP32 micro-controller that will execute the orders and forward them to the Arduino on the mechanical vehicle. ESP32 controls the developments of the mechanical vehicle as per got orders. The voice-controlled robot (VCR) moves advances, in reverse, left and right, and quits as indicated by the voice orders forward, in reverse, left, right and stop, respectively. We picked this as our endeavor as mechanical innovation has become a huge piece of our conventional lifestyle and moreover has a wide degree in the planning field. It's anything but's an essential occupation in the improvement of new advancement. © 2021 IEEE.

关键词： Internet of things

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Dual Layered Authentication Security for Sensitive Healthcare Data by Hadoop MapReduce 3

Dual Layered Authentication Security for Sensitive Healthcar...

引用

3rd international conference on Advances in Computing, Communication control and Networking, ICAC3N 2021

作者： Goyal, Deepti Kumar, Ankit Baba Mastnath University Computer Science Department Asthal Bohar Rohtak India

ISBN: (纸本)9781665438117

The healthcare industry is developing smart ways or systems to monitor one's own health through Big Data generated by Internet of Things (IoT) devices. The Internet of Things (IoT) provides a myriad of objectives that enable quick advancement in the healthcare field. Data created by those gadgets about a patient's ailment and diagnoses has become extremely sensitive, and its security has become a major concern for data professionals. Patients' data security has become increasingly and extremely relevant, allowing patients and other fitness-oriented individuals to freely use online gadgets in health care. For the security of sensitive Big Data, multiple symmetric encryption algorithms are used. In the near future, the role and significance of IoT devices in people's everyday lives will be greatly expanded. This study discusses a mechanism that provides double-step security by using a symmetric encryption technique that takes less time while encrypting and decrypting sensitive data. In addition, how is symmetric encryption used in healthcare to provide authentication security benefits to patients? IoT devices provide precise diagnosis of patients and patients in remote locations. © 2021 IEEE.

关键词： Internet of things

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Research on fault diagnosis of high voltage circuit breaker based on random forest optimized by powell-PSO

Research on fault diagnosis of high voltage circuit breaker ...

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Consumer Electronics and computer Engineering (ICCECE), 2021 IEEE international conference on

作者： Jun-wei Zhang Jun-yu Tian Xin Liu Long-fei Wu Peng Li Tong Wu Nari Technology Nanjing Control Systems Co. LTD Nanjing Nanjing China Construction Branch State Grid Jilin Electric Power Company Limited Chang Chun China

A Powell PSO optimized random forest fault diagnosis method for high-voltage circuit breakers is proposed, in order to improve the accuracy of the state identification of mechanical vibration signals of high-voltage circuit breakers. Firstly, the fault simulation model of high-voltage circuit breaker is built on MATLAB, and the closing process is simulated to collect vibration signals; Then the mechanical vibration signal of the circuit breaker is denoised by wavelet transform, and the eigenvalues are extracted; Secondly, Powell PSO fusion algorithm is constructed to optimize the random forest algorithm; Finally, the eigenvectors are input into the optimized random forest, and the classifier of Powell PSO optimized random forest algorithm is constructed, which finally realizes the high-precision identification of the mechanical fault state of high-voltage circuit breakers. The experimental results show that the new fault diagnosis method has high overall recognition rate and high application value.

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