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检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 777 条记录，以下是101-110 订阅

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5th international conference on VLSI, Communication and signal processing, VCAS 2022

5th International Conference on VLSI, Communication and Sign...

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5th international conference on VLSI, Communication and signal processing, VCAS 2022

ISBN: (纸本)9789819909728

the proceedings contain 67 papers. the special focus in this conference is on VLSI, Communication and signal processing. the topics include: Full-Duplex Spectrum Sensing with Imperfect CSI and Mobile Nodes;Sensitivity Enhancement of Kretschmann Configured Surface Plasmon Resonance Sensor with 2D Nanomaterial: MXene;metasurface-Based Tunable Radar Absorbing Structure for Broadband Applications;underwater Image Enhancement Using Color Correction and Fusion;Study and Analysis of three-Stage Single-Miller CMOS OTA;Stacked Bi-LSTM Network and Dual signal Transformation for Heart Sound Denoising;machine learning-Based FSOC Link Performance Estimation;Abnormality Detection in Heart Using Combination of CNN, RNN and U-Net;High Speed LVDS Driver Design with Fast Settling Common Mode Feedback Circuit;design and Analysis of Low Power Frequency Divider Circuit;static Single Phase Contention Pulsed Latch for Low Voltage Operation;design of Y-shaped Multiband Antenna Using the Parametric Approach for Wireless Networks;Design and Implementation of 1 × 4 & 4 × 4 RAM Using Quantum-Dot Cellular Automata;FPGA and ASIC-Based Design of Fast and Low Power SEC-DAEC and SEC-DAEC-TAEC Codecs;Reliable Implementation of Finite State machine for On-Board VLSI Designs;Performance Improvement of SAC-OCDMA FSO System Under Rain and Snow Conditions Using Different Zero Cross-Correlation Codes;Robust and Imperceptible Color Image Watermarking Using LWT, Schur Decomposition, and SVD in YCbCr Color Space;BER Efficiency of Outdoor Optics Links Using Hybrid-SIM with Pointing Errors Operating on Extreme Turbulence Regime;Design of three Slot-Based Multiband MIMO Circular Patch Antenna;An Imperceptible Semi-blind Color Image Watermarking Using RDWT and SVD;a Non-invasive Planar Resonant Microwave Sensor for Unknown Liquid Permittivity Estimation.

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Secure Localization Techniques in Wireless Sensor Networks Against Routing Attacks Using machine learning Models 5th

Secure Localization Techniques in Wireless Sensor Networks A...

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5th international conference on Soft Computing and signal processing, ICSCSP 2022

作者： Gebremariam, Gebrekiros Gebreyesus Panda, J. Indu, S. Department of Electronics and Communication Engineering Delhi Technological University Shahbad Daulatpur Main Bwana Road Delhi110042 India

ISBN: (纸本)9789811986680

Security is an essential hot research topic for detecting and localization of malicious nodes and improving the quality of service in wireless sensor networks (WSNs). WSNs are exposed to different routing attacks, including wormhole attacks, Sybil attacks, and blackhole attacks that manipulate the network resources and routing protocols, affecting the localization accuracy and quality of service in WSNs. this work proposed secure localization and detection of routing attacks in WSNs using hybrid optimized machine learning techniques with an average detection accuracy of 100% using binary classification with the application of cluster labeling K-means clustering technique. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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Prediction of Electric Vehicle Charging Stations Distribution Using machine learning 5

Prediction of Electric Vehicle Charging Stations Distributio...

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5th international conference on signal processing and Information Security, ICSPIS 2022

作者： El Rai, Marwa Chendeb Hadi, Sabina Abdul Damis, Haitham Abu Gawanmeh, Amjad University of Dubai College of Engineering and IT Department of Electrical Engineering Dubai United Arab Emirates

ISBN: (纸本)9781665492652

Electric vehicles (EV) are becoming more mainstream as consumer purchasing choices are in favor of this innovative technology. Hence, there is a need to install new electric vehicle charging stations (EVCS). thus, determining where new stations should be installed is an apparent prospective challenge. In this paper, we tackle the mentioned challenge by creating a dataset enabling us to predict where new EVCS should be be installed. machine learning models such as K-nearest neighbours, logistic regression, neural networks, and support vector machines can be applied to determine recommended EVCS installation places. City of Dubai located in United Arab Emirates (UAE) is selected to be the model of our case study. Population density, points of interest (POI), and the existence of security cameras are the features considered in this work. the performance of different machine learning models is evaluated using f1-score and accuracy metrics. Experiments show that the validation accuracy is 89% using K-Nearest Neighbors model. © 2022 IEEE.

关键词： Support vector machines

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Research on Coding Method of Microscopic Video signal Based on machine learning 5th

Research on Coding Method of Microscopic Video Signal Based ...

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5th EAI international conference on Advanced Hybrid Information processing (ADHIP)

作者： Gong, Hai-xiao He, Jie Wuzhou Univ Sch Data Sci & Software Engn Wuzhou 543002 Peoples R China Wuzhou Univ Guangxi Coll & Univ Key Lab Image Proc & Intellig Wuzhou 543002 Peoples R China

ISBN: (纸本)9783030945541;9783030945534

At present, the commonly used microscopic video signal coding methods have poor processing ability and low coding accuracy. therefore, this paper proposes a new micro video coding method based on machine learning technology. Firstly, the video coding processing architecture is established by intra prediction, inter prediction, transformation, quantization, entropy coding and loop filtering, and then the coding processing is realized by image segmentation, intra prediction and inter prediction, and the depth decision method is used for depth analysis. the experimental results show that this method can effectively improve the processing ability of microscopic video signal coding, and at the same time enhance the coding accuracy.

关键词： machine learning Microscopic video signal Video coding processing Depth decision

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Unveiling Hidden Patterns in Speech: Audio signal-Based Approach for Depression Detection 1

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5th international conference on Advances in Information Communication Technology and Computing, AICTC 2024

作者： Ghosh, Debadrita Karande, Hema Gite, Shilpa Symbiosis Institute of Technology AI & ML Department Pune India

ISBN: (数字)9789819761036

ISBN: (纸本)9789819761029

Detecting psychological disorders, particularly depression, is a complex and critical task within the realm of mental health assessment. this research explores a novel approach to improve the identification of psychological distresses, such as depression, by highlighting the subjectivity complexity, and biases inherent in traditional diagnostic techniques. Using audio data, and extracting such as voice characteristics and linguistic content from participant interviews, we developed a hybrid model that combines advanced machine learning processing and deep learning approaches. this study investigates the theoretical underpinnings, technical complexities, and practical applications of this model in the context of psychological disorder detection, with the goal of empowering mental health professionals and improving the lives of individuals facing psychological challenges. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Contrastive learning

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Book Genre Classification System Using machine learning Approach: A Survey 5th

Book Genre Classification System Using Machine Learning Appr...

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5th international conference on Soft Computing and signal processing, ICSCSP 2022

作者： Sethy, Abhisek Rout, Ajit Kumar Gunda, Chandra Routhu, Sai Kiran Kallepalli, Srinu Garbhapu, Geetha Department of Information Technology GMR Institute of Technology Srikakulam Rajam India Department of Computer Science & Engineering Silicon Institute of Technology Bhubaneswar India

ISBN: (纸本)9789811986680

the amount of complicated texts and documents that require a deeper understanding of machine learning techniques has expanded rapidly in recent decades. Several machine learning approaches have shown exceptional results in NLP. Complex models and non-linear data correlations help these learning systems function well. It is difficult for academics to discover appropriate text classification structures, designs, and procedures. Manually reading and classifying a book's category would be tedious. It takes a long time for a language beginner to absorb the complete text in order to discern its genre. Natural Language processing (NLP), which is commonly used nowadays, can help overcome this issue. It includes text classification and summarization. the book synopsis is input to the machine learning algorithms, which output the genre. this review includes text feature extraction, dimensionality reduction, algorithms, and evaluation. Finally, the limitations of each strategy are assessed, as well as their practicality. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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Extractive Text Summarization 5

Extractive Text Summarization

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5th IEEE international conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Kumar, Abhishek Delhi Technological University Department Of Computer Science And Engineering New Delhi India

ISBN: (纸本)9798350330861

the fields of artificial intelligence (AI), machine learning (ML), and data science have grown significantly over the past ten years, opening up a wide range of opportunities in sectors as varied as healthcare, banking, and transportation. Notably, there have been substantial developments in the field of Natural Language processing (NLP), which is a subfield of AI and ML. NLP involves the machine-based processing and understanding of human language. Among its various applications, text summarization holds prominence as it enables machines to condense lengthy texts into concise summaries. this project highlights the utilization of multiple extractive text summarization techniques, including Word Frequency, Lex, Luhn, Kl Summarizer, GPT-2 and BERT. the resultant extractive summaries are then evaluated against human-generated summaries using three distinct scoring methods: Rouge Score, BERT Score, and Mover Score. through this project, we demonstrate the efficacy of these techniques in generating summaries and assess their quality by comparing them against summaries produced by humans using the specified scoring metrics. © 2023 IEEE.

关键词： signal encoding

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Transfer learning Methods and their Application in Radar signal processing 5

Transfer Learning Methods and Their Application in Radar Sig...

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5th IEEE international conference on Big Data and Artificial Intelligence (BDAI)

作者： Yang, Liru Liu, Yongxiang Yang, Wei Natl Univ Def Technol Coll Elect Sci & Technol Changsha Peoples R China

ISBN: (数字)9781665470810

ISBN: (纸本)9781665470810

Transfer learning method uses the similarity of data, tasks, models in different domains and applies the knowledge from one domain to another domain. Traditional machine learning requires that the test and training data sets obey the same data distribution. In contrast, transfer learning can reuse the training samples of similar data distribution in different fields and improve new fields' learning and training effect. Currently, there are many studies on the theory of transfer learning, especially in the field of domain adaptability. this paper summarizes and analyzes the research progress of data distribution adaptation methods, feature selection methods, subspace learning methods, and deep transfer learning methods. then, the application of transfer learning in the radar field is further introduced. Finally, the future research direction of transfer learning is discussed.

关键词： transfer learning domain adaptation distribution adaptation feature selection method subspace learning method deep transfer learning method radar field

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Relevance calculation of users' document sending behavior under the network social platform 5

Relevance calculation of users' document sending behavior un...

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5th international conference on machine learning and Natural Language processing (MLNLP)

作者： Cheng Qian Zhang Youwei Xue Bing Ge Fangli Yao Wenqing Zhengzhou Xinda Inst Adv Technol Zhengzhou Peoples R China

ISBN: (纸本)9781450399067

the correlation calculation of online users' posting behavior is studied as the core part in the analysis and characterization of Internet user entity identity association. the paper will complete the processing of the information posted by the network users and train the bag-of-words model to obtain the feature vector of the posted information, and then use the distance formula to calculate the correlation of the posted behavior information, which can assist in the analysis and characterization of network user entity identity association and associate the identity relationship between multiple virtual users, so as to build a network user relationship network. the method in this paper is experimentally verified on the published data of WeChat public account, using three training models, Word2Vec, CNN and Seq2Seq. the results prove the effectiveness of the text method, and provide research ideas and method support for the analysis and characterization of network user entity identity associations.

关键词： correlation calculation network data Identity Correlation natural language processing

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Utilizing Support Vector machines for signal processing in Telecommunications 5th

Utilizing Support Vector Machines for Signal Processing in T...

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5th international conference on Data Science, machine learning and Applications, ICDSMLA 2023

作者： Mishra, Awakash Mehta, Deepak Arya, Rakesh Prasad, P.S. Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Karnataka Bengaluru India Department of Computer Science and Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India

ISBN: (纸本)9789819780426

SVMs had been effectively applied to various signal processing tasks in Telecommunications, along with goal detection and category in cognitive radio networks, channel estimation, exploiting spatial variety for multipath wireless conversation channels, interference cancellation, and era of feature vectors for sign type. In goal detection and category in Wi-Fi conversation networks, SVMs may be used to come across and classify specific types of wireless signals with an excessive diploma of accuracy. the input characteristic vectors are comprised of the signal’s spectrum and temporal features, and they are used for the education of the SVM classifier. In channel estimation, SVMs may be used to estimate the unknown channel parameters in Wi-Fi conversation channels with a low but suitable suggest-squared-blunders charge. that is viable via exploiting the diversity of more than one received signal replicas and the usage of the predicted channel parameters to improve signal reception. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wi-Fi

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