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检索条件"任意字段=2022 3rd International Conference on Signal Processing and Computer Science, SPCS 2022"

共 761 条记录，以下是41-50 订阅

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Study and design of a front-end of a UHF RFID Tag in 0.18 μm CMOS technology 3

Study and design of a front-end of a UHF RFID Tag in 0.18 μ...

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3rd IEEE international conference on Electronics, Control, Optimization and computer science, ICECOCS 2022

作者： Habibi, Sanae Bendali, Abdelhak Reda El Wardi, Abid Zarrik, Samia El Kobbi, Mouad Mohamed, Habibi Abdelkaer, Hadjoudja Ibn Tofail University Laboratory of Electronic Systems Information Processing Mechanics and Energy Kenitra Morocco

ISBN: (数字)9781665457231

ISBN: (纸本)9781665457231

This paper presents the study and design of a modulator (front-end) of a UHF RFID tag in CMOS technology. The analog front-end works like this: A rectifier extracts a DC voltage from the RF supplied by the tag. A voltage regulator follows the rectifier and its role is to obtain a stable supply voltage Vdd for the digital part and the analog front-end. In addition, the ASK demodulator (ASK: Amplitude Shift Keying) extracts the data symbols embedded in the carrier waveform (data input).Backscatter modulation is achieved by switching the input impedance between two reflection states determined by the data output signal. The main objective is to simulate a modulator of the load impedance by which the Tag radiates a modulated signal back to the RFID reader using ADS simulation software and TSMC RF CMOS 0.18μm process library. © 2022 IEEE.

关键词： Radio frequency identification (RFID)

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Research on Chinese word sense disambigution based on Prompt learning 3

Research on Chinese word sense disambigution based on Prompt...

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3rd international conference on computer science and Management Technology, ICCSMT 2022

作者： Gan, Ling Du, Xinrui Chongqing University of Posts and Telecommunications School of Computer Science and Technology Chongqing400065 China

ISBN: (纸本)9798350320404

Word sense disambiguation is an important research topic in natural language processing. Its purpose is to determine the word meaning of a polysemous word in different contexts. In order to improve the efficiency of disambiguation, a Chinese word sense disambiguation model PL-WSD based on prompt learning is proposed. The model uses the knowledge base HowNet to obtain the representation of each word meaning in polysemous words, uses the way of prompt learning to calculate the similarity score of each word meaning in a specific context, and obtains the word meaning with the highest score as the final result of polysemous words. Experiments show that PL-WSD model is greatly improved compared with other models. © 2022 IEEE.

关键词： Knowledge based systems

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Research on the segmentation of pension market based on K-means clustering algorithm 3

Research on the segmentation of pension market based on K-me...

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3rd international conference on computer science and Management Technology, ICCSMT 2022

作者： Wei, Xinyu Li, Xufang Shanghai University of Engineering Science School of Management Shanghai China

ISBN: (纸本)9798350320404

With the acceleration of the aging process and the extension of life expectancy, the community is increasingly concerned about the pension problem. In order to better serve the needs of the elderly, accurately match the right pension mode, help pension industry in China to achieve more accurate marketing, improve customer recognition and core competitiveness, this article through the questionnaire survey to collect the elderly data, the K-means clustering algorithm for data processing and analysis, and according to the clustering results of endowment group classification in detail. The study found that it was most appropriate to cluster the sample data into four categories, and put forward suggestions according to the characteristics of the four groups of people. © 2022 IEEE.

关键词： K-means clustering

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Dermatobot: An Image processing Enabled Chatbot for Diagnosis and Tele-remedy of Skin Diseases 3

Dermatobot: An Image Processing Enabled Chatbot for Diagnosi...

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Kohli, Shivansh Verma, Utkarsh Kirpalani, Vinay V Srinath, Ramamoorthy Pes University Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9781665494991

Diseases of dermatological nature have become quite common given the deteriorating environmental conditions, making visits to a dermatologist more frequent. However, a visit to a dermatologist may not always be very feasible as a result of which skin diseases may go untreated and this might become a significant problem in time. Dermatobot is a portable dermatologist for common skin diseases which aims at reducing skin ailments going untreated by providing a combined computer vision and NLP enabled diagnosis to skin diseases and suggesting out remedies for the diagnosed disease. Universal Sentence Encoders were used for similarity matching and an image classification model trained upon EfficientNetB4. The image classification model obtained a top-5 validation accuracy of 92%.Disclaimer: Dermatobot is not a replacement for dermatologists and only recommends mild remedies that the user can adhere to at his/her own avail. © 2022 IEEE.

关键词： Telemedicine

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Correlation Discriminator of signals in the Class of Fast Neural Networks 3

Correlation Discriminator of Signals in the Class of Fast Ne...

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3rd international conference on Neural Networks and Neurotechnologies, NeuroNT 2022

作者： Dorogov, Alexander Yu. Saint Petersburg Electrotechnical University "leti" Faculty of Computer Science and Technology Saint Petersburg Russia

ISBN: (纸本)9781665467766

The paper presents methods for constructing topology and parametric training of fast neural networks (FNN) for tasks of signal correlation measurements. A mathematical model of the FNN is described. The connection of fast algorithms with self-similar structures is noted. A method of multiplicative representation of arbitrary discrete functions is shown. Algorithms for constructing the FNN topology and training for implementing a correlation discriminator of signals are proposed. © 2022 IEEE.

关键词： Discriminators

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Research on Big Data computer Information processing 3

Research on Big Data Computer Information Processing

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3rd international conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC)

作者： Guan, Jiwen Guangdong Univ Sci & Technol Dongguan 523083 Guangdong Peoples R China

ISBN: (纸本)9781665454551

Nowadays, our human beings are developing with each passing day in science and humanities, especially in the increasingly fierce competition of modern science and technology with information technology as the core content. If we want to keep pace with The Times, we must master information *** a result, large-scale information has emerged. Based on this, this paper studies the computer information processing of big data. First of all, it briefly summarizes the relevant contents of the era of big data, then analyzes the challenges and opportunities of computer information processing technology in the era of big data, then discusses computer information processing technology in the era of big data, and finally looks forward to its future development. I hope it. Discussions in this article can promote people to have an in-depth understanding of this aspect.

关键词： big data computer information processing technology Information storage Information security

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Prediction of Iron Ore Spheroidity Based on Image Texture Features and PCA-SVR 3

Prediction of Iron Ore Spheroidity Based on Image Texture Fe...

引用

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

作者： Liu, DaiFei Wang, ShengYang Changsha University of Science and Technology School of Energy and Power Engineering Changsha China

ISBN: (纸本)9781665459112

Spheroidity is an important parameter to describe the granulation characteristics of iron ore. Traditionally, physical and chemical analysis methods are used to obtain the spheroidization of iron ore. However, these processes are time-consuming and labor-intensive, and it is difficult to control the accuracy of the results. In this study, image processing and neural networks are used to construct a support vector regression (SVR) iron ore sphericity prediction model from the perspective of information fusion. Three kinds of image texture feature extraction methods are used: Tamura texture feature, gray level co-occurrence matrix (GLCM), and gray level difference statistics (GLDS). Principal component analysis are used to dimensionality reduction of image texture feature parameters. Under the same operating conditions, the results using the SVR model with and without PCA are compared, and the prediction accuracy of these models for iron ore spheroidity are 96.7% and 79.8%, respectively. The results show that the model based on image texture features and PCA-SVR has excellent characteristics, such as fast operating time and high accuracy, for the prediction of iron ore spheroidity, has practical significance in guiding the sintering process of iron ore and can provide further efficient and accurate research on iron ore spheroidity in the future. © 2022 IEEE.

关键词： Principal component analysis

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Overlapped Pedestrian Detection Based on YOLOv5 in Crowded Scenes 3

Overlapped Pedestrian Detection Based on YOLOv5 in Crowded S...

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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： Guo, Weijie Shen, Nanbo Zhang, Tianze Hunan University of Technology Department of Computer Science and Technology Zhuzhou China China University of Geosciences School of Information Engineering Beijing China Beijing University of Technology School of Software Beijing China

ISBN: (纸本)9781665459112

Pedestrian detection in a crowded environment is challenging for vehicle intelligent driving systems. At present, pedestrian detection algorithms have achieved great performance in detecting well-separated figures. However, pedestrians are generally overlapped in crowded scenes, resulting in slow detection speed, low detection accuracy, and poor robustness in pedestrian detection technology. In this paper, the YOLOv5 algorithm is used for pedestrian detection. In the aspect of data pretreatment, Mosaic data enhancement, unified image size, adaptive anchor frame calculation, and other processing are carried out for ***5 can detect targets at multiple scales, and CIOU_Loss and DIOU_nms are applied to the YOLOv5 algorithm. It can improve the recognition ability of the occlusion target and has a good detection effect on the detection of the occlusion pedestrian target through the training network of amplified data set. The verification experiment shows that the pedestrian detection model based on YOLOv5 has great detection accuracy and recall rate in detecting covered pedestrians. © 2022 IEEE.

关键词： Feature extraction

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GPS and Real-Time computer-Vision based Intelligent Navigation System for Electric Vehicle 3

GPS and Real-Time Computer-Vision based Intelligent Navigati...

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3rd international conference on Innovations in science and Technology for Sustainable Development, ICISTSD 2022

作者： James, Binoj Bindu, S.J. College of Engineering Perumon Dept of Electrical and Electronics Engineering Kollam India

ISBN: (纸本)9781665499361

This paper aims to present the hardware design steps involved in developing an Autonomous Electric Vehicle prototype using computer Vision and GPS waypoint navigation. A Raspberry Pi is used as the main processing unit, the surrounding environment is sensed by cameras and ultrasonic sensors. A GPS and compass are used to navigate the vehicle. The vehicle will be able to identify road lanes, recognize traffic signals and signs and go to the required GPS coordinate autonomously without human intervention, without violating any traffic rules and reducing human errors. © 2022 IEEE.

关键词： Global positioning system

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An Architecture of Enhanced EMG signal Classification based on Multi-Agent System 3

An Architecture of Enhanced EMG Signal Classification based ...

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3rd international conference on Intelligent Engineering and Management, ICIEM 2022

作者： Jain, Reema Garg, Vijay Kumar Lovely Professional University Department of Computer Application Punjab Phagwara India Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India

ISBN: (数字)9781665467568

ISBN: (纸本)9781665467568

An Electromyography (EMG) signal provides reliable information and represents an important step towards man-machine communication to address neuro-muscular movements. The vital aspects of this research focus on data acquisition, signal pre-processing, feature extraction, and accurate classification to meet the practical challenges in terms of reliability. The recorded signals first undergo pre-processing in which the uploaded EMG signals are first segmented into clusters using K-means followed by a Genetic Algorithm (GA) that precisely extracts the rows that exhibit potential signal data. The multi-agent system is designed using a Support Vector Machine (SVM) with neural network architecture. This information of trained features deduced using SVM kernel function, also known as Support Vectors (SVs), is fed to Neural Network (NN) for the classification of EMG signals into two classes, namely, normal and pain. The performance of the proposed classification work is evaluated against the Electro- Myography-EMG dataset in terms of precision, sensitivity, f- measure, and accuracy. The simulation analysis over 1000 simulation rounds had demonstrated an average precision of 0.931, sensitivity of 0.915, f-measure of 0.923, and classification accuracy of 95.51%. The results illustrate a better classification accuracy when SVM support vectors are used by FFBPNN to learn the features of normal, and pain class in comparison to the existing EMG signal classification approaches. © 2022 IEEE.

关键词： Support vector machines

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