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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16439 条记录，以下是1861-1870 订阅

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A Vehicle Attitudes Measurement Method Based on MEMS IMU and Integrating Road Smoothness

A Vehicle Attitudes Measurement Method Based on MEMS IMU and...

引用

6th International conference on Intelligent Computing and Signal processing (ICSP)

作者： Haozhe Liu Yufan Wu Sujing Song Kunpeng Li Jianping Lan Sheng Tang College of Information Science and Technology Northwest University Xi'an Shaanxi China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Obtaining the accurate attitudes of vehicle is of great importance for safe operation and automatic driving. This paper researches a vehicle attitudes measurement method where the low-cost MEMS IMU devices are used, and proposes an improved attitudes measurement algorithm based on Mahony Complementary Filter. According to IRI (International Roughness Index) measured in real-time, the complementary filter coefficients are adjusted adaptively to achieve the purpose of high-precision measurement under different road conditions. The experimental verification on a self-developed prototype vehicle model indicates that the proposed method has better performance than other traditional methods on moving vehicle attitudes measurement.

关键词： Micromechanical devices Semiconductor device measurement Accuracy Roads Signal processing algorithms Filtering algorithms Signal processing Real-time systems Rough surfaces Synchronization

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Automatic Identification of the American Sign Language Using Machine Learning

Automatic Identification of the American Sign Language Using...

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Machine Learning and Autonomous systems (ICMLAS), International conference on

作者： Ravi Kishore Kodali Arindam Pattanayak Department of Electronics and Communication Engineering National Institute of Technology Warangal Warangal India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

Communication is essential, providing a means to express thoughts, emotions, and ideas. Sign language is a fundamental form of communication for those who are deaf, have hearing impairments, or are non-verbal. This research uses machine learning to develop an effective algorithm for identifying the alphabet in American Sign Language (ASL) through natural hand movements. The system combines image processing, machine learning, and artificial intelligence, especially a convolutional neural network (CNN), to translate ASL gestures into accurate and understandable output. After training the model on a dataset that includes sign language images, the results demonstrate the system's ability to identify hand gestures related to the English alphabet accurately.

关键词： Hands Training Deep learning Sign language Translation Accuracy Machine learning algorithms image processing Predictive models Convolutional neural networks

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A New Extrapolation Solution for MU-MISO Symbol-Level Precoding

A New Extrapolation Solution for MU-MISO Symbol-Level Precod...

引用

International conference on Wireless Communications and Signal processing (WCSP)

作者： Mu Liang Ang Li xiaoyan Hu Christos Masouros School of Information and Communications Engineering Xi'an Jiaotong University Xi'an China Department of Electronic and Electrical Engineering University College London London UK

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

Constructive interference (CI) precoding, which converts the harmful multi-user interference into beneficial signals, is a promising and efficient interference management scheme in multi-antenna communication systems. However, CI-based symbol-level precoding (SLP) experiences high computational complexity as the number of symbol slots increases within a transmission block, rendering it unaffordable in practical communication systems. In this paper, we propose a symbol-level extrapolation (SLE) strategy to extrapolate the precoding matrix by leveraging the relationship between different symbol slots within in a transmission block, during which the channel state information (CSI) remains constant, where we design a closed-form iterative algorithm based on SLE both for PSK and QAM modulation. In order to further reduce the computational complexity, a sub-optimal closed-form solution based on SLE is further developed. Extensive simulation results illustrate that the proposed algorithms can dramatically reduce the computational complexity and time complexity with only marginal performance loss, compared with the conventional SLP design methods.

关键词： Wireless communication Phase shift keying Extrapolation Quadrature amplitude modulation Precoding Simulation Symbols Signal processing algorithms Modulation Interference

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Recognition of Chinese Gong-Che Notation Characters Based on YOLOv8

Recognition of Chinese Gong-Che Notation Characters Based on...

引用

6th International conference on Intelligent Computing and Signal processing (ICSP)

作者： Yuqian Zhang Liumei Zhang Yuanjiao Hu Tengzhuo Ju School of Computer Science Xi'an Shiyou University Xi’ an China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

Although Optical Music Recognition (OMR) technology has matured for general music notation like staff notation, it is rarely used in traditional Chinese music notation, such as Gong-che notation. It is difficult to accurately identify Chinese characters in Gong-che notation with traditional methods. To address this, we propose the YOLOv8 method to enhance Gong-che notation characters recognition accuracy. We adopt lightweight and medium-weight YOLOv8 models and explore the optimal network structure to enhance the generalization ability of characters recognition. Data augmentation techniques such as image translation, rotation and noise processing are used to solve the diversity of characters recognition and enhance the robustness of the model. Experimental results demonstrate that the YOLOv8m model achieved an accuracy improvement from 74.95% to 84.19% in Gong-che notation characters recognition, surpassing the performance of the YOLOv8n model. This validates the remarkable performance of the YOLOv8 network in Gong-che notation characters recognition tasks.

关键词： Accuracy Optical character recognition Noise Signal processing algorithms Optical imaging Data augmentation Rhythm Robustness Character recognition Optical signal processing

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Performance Optimization of Machine Learning-Driven image Recognition algorithms for iOS Mobile Platforms

Performance Optimization of Machine Learning-Driven Image Re...

引用

International conference on Control systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Ibragim Mamadaev Muslim Mamadaev Bauman Moscow State Technical University Moscow Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

Today., mobile devices play an important role in the daily life of every person., without which many can no longer imagine their lives. One of the key technologies leading to significant benefits for mobile applications is machine learning. Optimization of machine learning algorithms for mobile devices is an urgent and important task., it is aimed at developing and applying methods that will effectively use the limited computing resources of mobile devices. The paper discusses various ways to optimize image recognition algorithms on mobile devices., such as quantization and compression of models., optimization of initial calculations. In addition to ways to optimize the machine learning model itself., various libraries and tools for using this technology on mobile devices are also being considered. Each of the described methods has its advantages and disadvantages., and therefore., in the results of the work., it is proposed to use not only a combination of the described options., but also an additional method of parallelization of image processing processes.

关键词： Performance evaluation Support vector machines Machine learning algorithms image recognition Recurrent neural networks Optimization methods Generative adversarial networks Mobile handsets Libraries Convolutional neural networks

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FPGA Based image processing: A Comparative Study of Software-Centric and Hardware-Accelerated Approaches

FPGA Based Image Processing: A Comparative Study of Software...

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Smart Electronics and Communication systems (ISENSE), International conference on

作者： P N Parameswaran S Janardan Siddharth R Nair Thejaswitha T K Nikhil M Adersh V R Dept of Electronics and Communication College of Engineering Trivandrum Thiruvananthapuram India

ISBN: (数字)9798331528126

ISBN: (纸本)9798331528133

This work compares two different approaches to image processing algorithm implementation in Zynq Zybo and Zedboard Field Programmable Gate Array (FPGA) boards. There are three main phases for the study, namely, Hardware-Accelerated image processing (HAIP), Software-Centric image processing (SCIP), and an in-depth analysis of their corresponding performance metrics. image processing algorithms were implemented in the SCIP phase, exclusively using the Zynq processing System (PS). On the other hand, the HAIP phase comprised creating distinct Intellectual Properties (IPs) for image processing tasks and integrating them with the Zynq PS through Direct Memory Access (DMA) and the Advanced eXtensible Interface (Axi) *** all assessed techniques, HAIP considerably outperformed SCIP in terms of processing time, for different image sizes, across both Zynq Zybo and Zedboard. On the other hand, as SCIP is software-centric, it showed minimal resource utilization and lower power consumption than HAIP, which showed higher resource utilization and power consumption. However, both methods produced processed images that were similar, highlighting the stability and dependability of FPGA-based image processing implementations. A comparative analysis between Zynq Zybo and Zedboard reveals insights into how different FPGA architectures impact the performance and resource utilization of image processing implementations. This work offers insights into the trade-offs between hardware-accelerated and software-centric approaches to image processing on FPGA platforms, guiding future design decisions for practical uses.

关键词： Hands Measurement Power demand image processing Intellectual property Logic gates Stability analysis Robustness Resource management Field programmable gate arrays

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Design and Simulation Analysis of a Ship Heading Controller

Design and Simulation Analysis of a Ship Heading Controller

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Intelligent Control, Measurement and Signal processing and Intelligent Oil Field (ICMSP), International conference on

作者： Lina Zhao Lei Lou Bin Shang College of Intelligent Manufacturing Dalian Vocational & Technical College Dalian China

ISBN: (数字)9798331516550

ISBN: (纸本)9798331516567

With China's rising status in global maritime affairs, the safety of ship operations, as the primary means of maritime transportation, has become increasingly prominent. Given that ships face multiple degrees of freedom of external disturbances while navigating at sea, leading to poor stability during voyages, this study selects seafaring vessels as its research subject. Based on Backstepping design theory and leveraging the characteristics of nonlinear control algorithms, it employs a reverse recursive approach to design a nonlinear heading controller suitable for ships. Through simulation verification, the precise control of the ship’s direction demonstrates the controller’s superior performance in maintaining a predetermined course in complex marine environments, highlighting its effectiveness in controlling nonlinear motion trajectories.

关键词： Navigation Signal processing algorithms Transportation Sea measurements Signal processing Control systems Stability analysis Trajectory Safety Marine vehicles

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A Comparative Study of the Performance of Personnel Detection based on Visible and Infrared images 4

A Comparative Study of the Performance of Personnel Detectio...

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4th International conference on Video, Signal and image processing, VSIP 2022

作者： Liu, Futao Li, Zhenling Wan, Yuezhong Cao, Weida Ma, Duanwei Li, xiaolei Yan, Peng Liaocheng Power Supply Company State Grid Corporation of China China Shandong University School of Control Science and Engineering China Shandong TCCA Information Technology Research Institute China

ISBN: (纸本)9781450397810

Personnel security has always been a hot topic of research especially in power systems. Effective detection of people in power scenes has become a high priority. Currently, algorithms for personnel detection have been developed considerably, and they are mainly used for visible images. Since infrared images imaged by thermal radiation can detect living blood creatures easily, they can be used in personnel detection at night. To investigate the effect of visible and infrared images on the performance of personnel detection algorithms in different environments, this thesis uses two object detection algorithms, YOLOv5 and Faster RCNN, to train personnel detection models for visible daytime, visible nighttime, infrared daytime and infrared nighttime datasets respectively. Comparative experiments are conducted to quantitatively and qualitatively analyze the performance advantages and disadvantages of the personnel detection algorithms for visible images and infrared images during the day and night. The experimental results for both models consistently show that the visible images are similar to the infrared images during daylight hours with a good target detection model, the visible image is slightly better in performance. While the infrared image is significantly better than the visible image at night, and the mAP@0.5 can be improved by 0.2. For small human target detection, the infrared image has a significant advantage over the visible image at night, with an average detection size reduction of 48.0% and a minimum detection size reduction of 64.6%. © 2022 ACM.

关键词： image enhancement

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Superquadric Modeling Method of 3D Object Based on Invasive Weeds Optimization and Levenberg-Marquardt algorithms

Superquadric Modeling Method of 3D Object Based on Invasive ...

引用

image processing and Media Computing (ICIPMC), International conference on

作者： Lin Wang Donghan Ma Xuan Duan Shengmei Chen Boyue Duan Cheng Liu Pu Zhang School of Information Science and Technology Northwest University Xi’an China School of Information Engineering Xi’an Mingde Institute of Technology Xi’an China

Because of the problem of insufficient parameter fitting accuracy of superquadric modeling method based on Levenberg-Marquardt (LM) algorithm, a superquadric modeling method of 3D object based on invasive weed optimization (IWO) algorithm and LM algorithm is proposed. First, according to the distance relationship between each point in point cloud and the superquadric, a nonlinear optimization model for superquadric parameter estimation of 3D object is established. Then, to obtain the initial values of superquadric fitting parameters, the IWO algorithm is adopted to optimize the optimization model. After that, LM algorithm is also adopted to optimize the optimization model, and estimation values of superquadric fitting parameters of 3D object can be obtained. Thus, the superquadric model of 3D object of the given point cloud can be established. The experimental results show that the proposed method can yield highly accurate superquadric fitting parameters, and can effectively suppress the influence of measurement noise on modeling accuracy as well.

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FPGA-based Improved Canny Edge Detection System

FPGA-based Improved Canny Edge Detection System

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Information Technology,Big Data and Artificial Intelligence (ICIBA), International conference on IEEE International conference on

作者： Zhang Huan Wang Yaxin Wang Shuang Liu Zhihao Chen Panyu Wang Fangjuan School of Electronic Engineering Tianjin University of Technology and Education Tianjin China

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

In order to address the issues associated with the classic Canny operator, such as high computational load, incomplete edge information capture, and poor real-time performance, an improved multi-directional Canny edge detection method is proposed for using in service robot navigation systems. This method collects image information through the OV5640 camera, preprocesses the image after grayscale processing combined with mixed multiple filtering, and then performs eight directional adaptive threshold edge detection based on the classical Canny operator. After image enhancement, it runs on the FPGA chip. It can be seen from the experimental results that compared with the classic edge detection algorithm, the improved Canny operator has significantly improved the detection effect and can efficiently process the edges of various complex images in real time, providing a feasible solution for real-time image processing in the FPGA field.

关键词： Thresholding (Imaging) Service robots Navigation image edge detection Robot vision systems Noise Filtering algorithms Real-time systems Field programmable gate arrays image enhancement

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