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

共 783 条记录，以下是391-400 订阅

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Vehicle Localization with Surveillance Cameras 5

Vehicle Localization with Surveillance Cameras

引用

5th international conference on Vision, Image and signal processing (ICVISP)

作者： Kong, Qi Zhang, Liangliang Xu, Xin JD com Mountain View CA 94043 USA JD com Beijing Peoples R China

ISBN: (纸本)9781665407700

Vehicle localization is an important problem in autonomous driving research. Main stream methods use sensors on the vehicle with a SLAM algorithm, yet it has disadvantage on safety, cost and global intelligence comparing to sensing from infrastructure, especially surveillance cameras which are already pervasive in public urban area. To better address these challenges, this paper, for the first time, uses multiple surveillance cameras for vehicle localization. In this paper, a flexible two-stage framework for vehicle localization with surveillance cameras is introduced. Flexible deploying is its advantage. With first stage deploying on the camera local computing and second stage on the cloud, it can runs on limited bandwidth and computing conditions. Two potential directions of solutions under the framework are proposed. One is using instance mask as intermediate information, another is using key points of the vehicle.

关键词： Autonomous Driving Vehicle Localization Surveillance Cameras machine learning

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machine learning Based 5G RAN Slicing for Channel Evaluation in Mobile State 9th

Machine Learning Based 5G RAN Slicing for Channel Evaluation...

引用

9th international conference on signal and Information processing, Network and Computers, ICSINC 2021

作者： Zhang, Fangpei Jing, Xiaojun Mu, Junsheng Zhu, Jia Li, Bohan Information Science Academy of China Electronic Technology Group Corporation Beijing100086 China School of Information and Communication Engineering Beijing University of Post and Telecommunications Beijing100876 China University of Southampton Southampton United Kingdom

ISBN: (纸本)9789811947742

the number of mobile broadcast users has increased significantly because of evolved multi-media broadcast multicast services (eMBMS). According to the above reasons, machine learning technology is introduced into 5G RAN slices to forecast the state of communication channel in a mobile scene. We propose a new architecture not only including convolutional neural network (CNN), but also fusing long short-term memory network (LSTM) to implement channel estimation, simultaneously demonstrate the performance of our proposed scheme with simulation results. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Channel estimation

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A Review of Image Enhancement Methods Based on Stochastic Resonance of Neuronal Networks

A Review of Image Enhancement Methods Based on Stochastic Re...

引用

Pattern Recognition and machine learning (PRML), IEEE international conference on

作者： Ximin Sun Pingjuan Niu Yong Li Xiaoming Li Bingzhen Zhao Bin Zhang Dan Liu Bo Sun Tiangong University Laboratory of Metaverse in Electric Power Industry State Gride Ecommerce Technology CO.LTD Tian'jin China Laboratory of Metaverse in Electric Power Industry Tiangong University Tian'jin China Laboratory of Metaverse in Electric Power Industry State Gride Ecommerce Technology CO.LTD Tian'jin China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Stochastic resonance has always been a research hotspot in the field of image processing. the ability of the nervous system to detect signals is closely related to nonlinear and collective behavior in neural mediators. Neuronal noise is the most significant factor influencing this ability, and it is a natural endogenous fluctuation in brain activity. Experimental and theoretical studies have shown that noise is beneficial, not harmful, for the normal functioning of the nervous system. In this regard, it is generally agreed that noise of appropriate intensity can participate in the rhythmic activity of the brain, and that noise-induced oscillations enhance the performance of weak signal processing, especially when the frequency of the signal is approximately noise-induced rhythmic oscillations. this behavior in the biological nervous system can be explained by the concept of “stochastic resonance”. Correspondingly, the stochastic resonance mechanism of neurons is used to denoise the image, which has a good effect. In this paper, we first introduce an image processing method using random resonance of neurons. then, the commonly used evaluation indicators in the field of image processing are sorted out. Finally, the development trend of image processing using random resonance of neurons is prospected.

关键词： Reviews Stochastic resonance Noise Neurons Resonant frequency machine learning Market research Pattern recognition Oscillators Image enhancement

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Fast Node Selection of Networked Radar Based on Transfer Reinforcement learning 5th

Fast Node Selection of Networked Radar Based on Transfer R...

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5th IFIP TC 12 international conference on Intelligence Science, ICIS 2022

作者： Cao, Yanjun Wang, Yuan Guo, Jingjing Han, Li Zhang, Chao Zhu, Jin Zhang, Tianyang Zhang, Xiangrong The 54th Research Institute of China Electronics Technology Group Corporation Beijing China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Shaanxi Xian710071 China National Laboratory of Radar Signal Processing Xidian University Xian710071 China

ISBN: (纸本)9783031149023

the networked radar system can synthesize different echo signals received by various radars and realize the cooperative detection of multiple radars, becoming more and more critical for data fusion sharing and network collaboration. However, due to the large number and wide range of nodes in the networked radar system, there exists a redundancy problem in radar node assignment, which causes additional resource consumption and slows down the task execution speed of radar node selection. To solve the above problem, this paper proposes a fast radar node selection method based on transfer reinforcement learning to quickly select the optimal and minimum node resources. the proposed method devises a novel reward function for the Monte Carlo Tree and a different termination state of iteration to select the minimize the number of radar nodes. In order to further accelerate the selection of radar nodes, transfer reinforcement learning is presented to fully leverage the previous knowledge. Experimental results show that our proposed method can quickly select the optimal and minimum radar nodes in a brief period, significantly improving the speed of radar node selection in the networked radar. © 2022, IFIP international Federation for Information processing.

关键词： Reinforcement learning

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A Quick Overview of Recent Developments in Image Restoration using machine learning

A Quick Overview of Recent Developments in Image Restoration...

引用

India Council international Subsections conference (INDISCON), IEEE

作者： Neelam Kumari Isha Kansal Preeti Sharma Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350376753

ISBN: (纸本)9798350376760

Digital images are gradually getting importance in every industry, including computer science, medical, communications, transport, security, and surveillance. Degraded Images can be restored from a variety of distortions. Distortions occur due to malfunctioning imaging equipment transmission channels, atmospheric and environmental conditions, etc. Image restoration techniques have applications across various domains like image processing, data mining, and predictive analysis. Today machine learning is used in almost every area by taking into consideration its excellence efficiency, decision making, to automate task and to retrieve pertinent data for analysis. In an effort to solve issues, numerous academics, mathematicians, and programmers have conducted research and used a variety of machine learning techniques. this paper centers on a comprehensive overview of machine learning, techniques used for image restoration methodologies. the purpose of the study is to compare evolution of various parameters like Peak signal to Noise Ratio (PSNR), Structure Similarity Index Matrix (SSIM), Mean Structure Similarity Index Matrix (MSSIM), Mean Square Error (MSE) and Natural Image Quality Evaluator (NIQE) between machine learning (ML) and traditional techniques.

关键词： PSNR Surveillance Noise reduction machine learning Distortion Image restoration Indexes Security Predictive analytics Smart phones

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Real-Time signal processing using AI Integrated Framework for Color and Drawing in Gesture Recognition 5

Real-Time Signal Processing using AI Integrated Framework fo...

引用

5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Lavania, Geerija Arya, Vivek Sharma, Neha Rashid, Mamoon Akram, Shaik Vaseem JECRC Artificial Intelligence & Data Science Department Rajasthan Jaipur India Dept of Electronics and Communication Engineering Haridwar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Vishwakarma University Department of Computer Engineering Pune India Uttaranchal Institute of Technology Uttaranchal University Dehradun India

ISBN: (纸本)9798350398267

In the realm of image processing and pattern recognition, writing with gestures in the air has grown in popularity and difficulty over the past few years. It contributes significantly to the creation of automation processes and can improve human-machine communication in a range of systems. Many studies focus on cutting-edge methods and techniques that will expedite processing while preserving a high level of identification accuracy. Internally, the area of computer vision considers object tracking to be crucial. Object tracking techniques are credited to modern computers, easy access to good-looking, affordable video cameras, and automated video analytics requirements. the video analysis technique generally consists of three fundamental steps: first, recognizing the object, second, tracking its movement from frame to frame, and third, assessing the behavior of that object. Each of the four takes into account a separate issue: choosing the best item representation, choosing the tracking function, purchasing the item, and tracking the item. Numerous real-world applications, such as autonomous monitoring, video identification, and vehicle navigation, depend heavily on object-tracking algorithms. this area is utilized by the research, which focuses on it to create a prospective text-to-text converter transition. this Research occasionally works as a freelance journalist. Your fingerprint will be tracked by a computer. the created text can be copied and used for a variety of things, including emails and SMS. For the deaf, it will be a potent means to establish this connection. By removing the need for writing, an efficient communication system decreases the use of the phone and laptop. © 2022 IEEE.

关键词： Computer vision

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Development of a Hummed-Based Query System for Music Retrieval 5

Development of a Hummed-Based Query System for Music Retriev...

引用

5th IEEE international conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Sanya, Oluwafemi A. Oguntimilehin, Abiodun Abiola, Oluwatoyin Badeji-Ajisafe, Bukola Adebusola, Tope-Oke Shonuga, Folakemi Afe Babalola University Department of Computing Ekiti State Ado Ekiti Nigeria

ISBN: (纸本)9798331542559

this research aims to improve query by humming (QBH) systems, enabling users to find music by humming a tune into a device. the project uses optimized database indexing, advanced machine learning techniques, and signal processing to process diverse humming inputs. the prototype, developed using a Laravel-based web application and Python, is expected to improve music discovery and user interaction, laying the groundwork for future MIR systems. © 2024 IEEE.

关键词： Audio signal processing

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σ-Convergence of Fourier series & its Conjugate series

σ-Convergence of Fourier series & its Conjugate series

引用

international conference on Multimedia, signal processing and Communication Technologies, (IMPACT)

作者： K. M. Sahu Soni Narendra Kumar Alok Aggarwal Prananath (Autonomous) College Utkal University Odisha India Department of Mathematics NIET NIMS University Jaipur India SoCS UPES Dehradun UK India

ISBN: (纸本)9781665476485

Fourier series is one of the important domain in the applications in science and technology. In the work σ-Convergence of Fourier series & its Conjugate series are explored which will be helpful to apply the results in the domain of bio medical analysis and implementation for smooth curve. the objective of this paper is to obtain certain criteria for the σ- convergence of Conjugate series of a Fourier series.

关键词： Industries Instruments Quantum mechanics machine learning signal processing Optics Software

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Employing Information theoretic Metrics with Data-Driven Occupancy Detection Approaches: A Comparative Analysis

Employing Information Theoretic Metrics with Data-Driven Occ...

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international conference on signal processing and Information Security (ICSPIS)

作者： Aya Nabil Sayed Ridha Hamila Yassine Himeur Faycal Bensaali Department of Electrical Engineering Qatar University Doha Qatar College of Engineering and Information Technology University of Dubai Dubai UAE

ISBN: (纸本)9781665492669

Building occupancy data helps increase energy management systems’ performance, enabling lower energy use while preserving occupant comfort. the focus of this study is employing environmental data (e.g., including but not limited to temperature, humidity, carbon dioxide (CO 2 ), etc.) to infer occupancy information. this will be achieved by exploring the application of information theory metrics with machine learning (ML) approaches to classify occupancy levels for a given dataset. three datasets and six distinct ML algorithms were used in a comparative study to determine the best strategy for identifying occupancy patterns. It was determined that both k-nearest neighbors (kNN) and random forest (RF) identify occupancy labels with the highest overall level of accuracy, reaching 97.99% and 98.56%, respectively.

关键词： Measurement Radio frequency Temperature distribution machine learning algorithms signal processing algorithms Information security signal processing

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Multi-speaker Emotional Speech Synthesis Based on Self-Supervised Speech Representations

Multi-speaker Emotional Speech Synthesis Based on Self-Super...

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Pattern Recognition and machine learning (PRML), IEEE international conference on

作者： Mingming Yin Zhihua Huang Kexin Lu Haiyang Zhou School of Computer Science and Technology Xinjiang University Urumqi China Key Laboratory of Signal Detection and Processing School of Computer Science and Technology Xinjiang University Urumqi China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

In recent years, emotional speech synthesis has shown considerable progress. However, some existing emotional speech synthesis methods only model emotion from a single scale, resulting in only global or average emotional expression, unable to synthesize significant emotional speech. In this paper, we propose a multi-scale multi-speaker emotional speech synthesis method based on self-supervised speech model HuBERT. Firstly, the emotion information is extracted from the feature extractor HuBERT. Secondly, the extracted emotion information is modeled by coarse-grained emotion modeling and fine-grained emotion modeling respectively to obtain utterance-level emotion embedding and phoneme-level emotion embedding. through subjective and objective evaluation, we verify that the method is significantly better than the comparison model in terms of speech quality and emotional expression.

关键词： Speech recognition machine learning Feature extraction Speech synthesis Data mining

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