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检索条件"任意字段=IEEE International Conference on Signal Image Technology and Internet Based Systems"

共 20484 条记录，以下是611-620 订阅

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Customized CNN Architecture for ECG image-based Classification of Cardiovascular Diseases 1

Customized CNN Architecture for ECG Image-Based Classificati...

引用

1st international conference on Software, systems and Information technology, SSITCON 2024

作者： Akula, Chinni Krishna Mondal, Sourav Manyam, RevanthSaiKumar Akkineni, Hanish Chandra Narayan Hemanth, Betha Appikatla, Veera Tharaka Siva Rama Krishna Vfstr Deemed to Be University Department of Cse Guntur India

ISBN: (纸本)9798350352931

Outbreaks Cardiovascular diseases (CVDs) are still the main reason behind deaths globally;because they have a great effect on the total disease burden. As of recent estimates, approximately 32 percent of all global deaths are attributed to cardiovascular diseases, which translates to around 18.6 million deaths annually. Electrocardiography (ECG) is a fundamental tool in cardiology, traditionally analyzed in its raw signal format. However, recent advancements in machine learning and image processing suggest that analyzing ECG data as images might offer superior predictive capabilities for cardiovascular events. CNN models are especially having a more notable impact in this field. In this perspective, we have used ECG images and made improvements using Convolutional neural networks and outperformed the existing models with 98 percent accuracy. Xception model is the one that served as our base upon which we made some personal modifications resulting in a customized Convolutional Neural Network (CNN) to conduct this research. © 2024 ieee.

关键词： Convolutional neural networks

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A REDUCED-REFERENCE QUALITY ASSESSMENT METRIC FOR TEXTURED MESH DIGITAL HUMANS 49

A REDUCED-REFERENCE QUALITY ASSESSMENT METRIC FOR TEXTURED M...

引用

49th ieee international conference on Acoustics, Speech, and signal Processing (ICASSP)

作者： Zhang, Zicheng Zhou, Yingjie Li, Chunyi Fu, Kang Sun, Wei Liu, Xiaohong Min, Xiongkuo Zhai, Guangtao Shanghai Jiao Tong Univ Inst Image Commun & Network Engn Shanghai Peoples R China

ISBN: (纸本)9798350344868;9798350344851

In an era where 3D Digital Humans (DHs) are becoming increasingly prevalent in fields like gaming, automotive, and the metaverse, the demand for high DH visual quality is rising. This paper presents the first-ever reduced-reference (RR) quality assessment metric tailored specifically for textured mesh DHs, aiming to optimize transmission systems and improve Quality of Experience (QoE) for viewers in resource-constrained environments. Four critical geometric curvature-related attributes and two texture-related indicators are computed, which are then statistically analyzed and utilized in a Support Vector Regression (SVR) model for robust and efficient quality prediction. Experimental results confirm that our method outperforms existing full-reference (FR) metrics, making it an invaluable tool for the future of 3D DHs in various applications. The code is available at https://***/zzc-1998/RR-DHQA.

关键词： Quality assessment 3D digital humans textured mesh reduced-reference

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image edge detection based on improved ant colony algorithm 6

Image edge detection based on improved ant colony algorithm

引用

6th international conference on Intelligent Control, Measurement and signal Processing, ICMSP 2024

作者： Yan, Yuehao Hui, Juan Kong, Gaohui Wang, Shuaishuai Feng, Liyi Zhao, Yujie State Grid Henan Electric Power Company Xingyang Power Supply Company Xingyang China Zhengzhou Xinda Advanced Technology Research Institute Zhengzhou China

ISBN: (纸本)9798331516550

image edge detection is a necessary work in object recognition, feature extraction and structure analysis. Firstly, an improved ant colony algorithm is proposed to solve the problems of partial path selection, low accuracy and low efficiency of traditional ant colony algorithm. The initial pheromone, heuristic function, pheromone update rule and state transition parameters of ant colony algorithm were improved. Finally, the experimental simulation verifies that two classical images are selected to carry out adaptive edge extraction, and the edge detection effect is compared with the traditional detection algorithm. Experimental results show that the improved algorithm can achieve complete and continuous image edge extraction, and verify the effectiveness of the algorithm. © 2024 ieee.

关键词： Ant colony optimization

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Low-Power Single-Slope ADC with a Replica Comparator for Always-on CIS Applications 21

Low-Power Single-Slope ADC with a Replica Comparator for Alw...

引用

21st ieee Interregional NEWCAS conference (NEWCAS)

作者： Lee, Hohyeon Song, Minkyu Kim, Soo Youn Dongguk Univ Dept Semicond Sci Seoul 04620 South Korea

ISBN: (纸本)9798350300246

This paper presents a low-power single-slope analog-to-digital converter (SS-ADC) for always-on complementary metal-oxide-semiconductor (CMOS) image sensor applications. The proposed design features a pixel-signal-prediction-based comparator comprising a main comparator and a replica comparator. The comparator generates a prediction signal based on the difference of auto-zeroed voltage derived from static current differences of two comparators, finally resulting in the reduction of the number of counter toggles. In addition, for further reduction of power consumption, the second-stage amplifier in the main comparator utilizes the proposed positive-feedback bias-sampling technique to cut off the current path after the comparison. The proposed 11-bit SS-ADC is implemented using a 110-nm CMOS process, has a resolution of 640 x 480, and operates at a frame rate of 299 frames per second. Simulation results demonstrate that the reduction of the power consumption of SS-ADC with the proposed comparator is about 65%. In addition, we obtained the total power consumption per column of 13.1 mu W and a figure of merit of 44.6 fJ/conv.-step.

关键词： image sensor Low-power comparator Pixel-signal-based prediction Positive-feedback bias sampling Replica comparator Single-slope analog-to-digital converter Two-step counter

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mmSense: Detecting Concealed Weapons with a Miniature Radar Sensor 48

mmSense: Detecting Concealed Weapons with a Miniature Radar ...

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48th ieee international conference on Acoustics, Speech and signal Processing, ICASSP 2023

作者： Mitchell, Kevin Kassem, Khaled Kaul, Chaitanya Kapitany, Valentin Binner, Philip Ramsay, Andrew Faccio, Daniele Murray-Smith, Roderick University of Glasgow School of Physics and Astronomy G12 8SU United Kingdom University of Glasgow School of Computing Science G12 8RZ United Kingdom

ISBN: (纸本)9781728163277

For widespread adoption, public security and surveillance systems must be accurate, portable, compact, and real-time, without impeding the privacy of the individuals being observed. Current systems broadly fall into two categories - image-based which are accurate, but lack privacy, and RF signal-based, which preserve privacy but lack portability, compactness and accuracy. Our paper proposes mmSense, an end-to-end portable miniaturised real-time system that can accurately detect the presence of concealed metallic objects on persons in a discrete, privacy-preserving modality. mm-Sense features millimeter wave radar technology, provided by Google's Soli sensor for its data acquisition, and TransDope, our real-time neural network, capable of processing a single radar data frame in 19 ms. mmSense achieves high recognition rates on a diverse set of challenging scenes while running on standard laptop hardware, demonstrating a significant advancement towards creating portable, cost-effective real-time radar based surveillance systems. © 2023 ieee.

关键词： mmWave radars Real-time signal processing Vision Transformer

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A Micro-Doppler Analysis Method With Joint Parameter Estimation and signal Separation based on MIMO Array 2

A Micro-Doppler Analysis Method With Joint Parameter Estimat...

引用

2nd ieee international conference on signal, Information and Data Processing, ICSIDP 2024

作者： Shao, Yuyang Ma, Hui Liu, Hongwei Xidian University National Key Laboratory of Radar Signal Processing Xi'an China

ISBN: (纸本)9798331515669

In traditional human micro-Doppler signal applications, people usually move towards or away from the radar. There may be more situations in reality. This paper explores a new type of human micro-Doppler signal application and proposes a corresponding processing algorithm. In the new application, multiple input multiple output (MIMO) radar is used to replace traditional real aperture radar to reduce costs. At the same time, MIMO radar observes human motion on the side of the human body to obtain micro-Doppler curves. Compared to traditional applications, the new application can better serve security checks and human screening. based on the wavenumber domain transformation, L-statistic, and the image contrast maximization, this paper proposes an algorithm for Joint Parameter Estimation and signal Separation (JPESS) to analysis the micro-Doppler curves with translational phase under the side view. In this paper, the L-statistic algorithm is used to separate signals into rigid body parts and micro motion parts. By maximizing the image contrast, JPESS can utilize the separated signal of rigid body parts for optimal estimation of the speed and acceleration. After using estimated parameters to compensate for the micro-Doppler curve and searching for parameters by minimizing the total energy of the time-frequency map, the parameters of each micro motion part can be obtained sequentially. Simulations have verified that the algorithm can obtain human motion parameters and separate micro motion parts' signals with high accuracy and strong robustness. © 2024 ieee.

关键词： Population statistics

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Design of LoRa Communication Protocol for image Transmission 8

Design of LoRa Communication Protocol for Image Transmission

引用

8th international conference on Intelligent Computing and signal Processing, ICSP 2023

作者： Gao, Han Huang, Zhangqin Zhang, Xiaobo Huang, Ling Beijing University of Technology Beijing Engineering Research Center for IoT Software and System Beijing China

ISBN: (纸本)9798350302455

With the expansion of IoT application scenarios, the demand for edge IoT devices with integrated video analysis capabilities is gradually increasing. In remote areas where cellular base stations cannot reach, a low-cost wireless communication self-organizing network is urgently needed to transmit video processing results and images. LoRa has strong anti-interference performance and relatively high transmission rate, which is suitable for completing delay-tolerant information transmission. However, the traditional LoRaWAN protocol has low efficiency in image transmission. This paper proposes a multi-packet transmission communication protocol based on LoRa, which reduces the time for traditional communication protocol confirmation and processing, and focuses more on the image transmission of LoRa. Experimental results show that the multi-packet transmission protocol achieves relatively high communication efficiency. © 2023 ieee.

关键词： image communication systems

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Research on image Edge Detection Method based on Wolf King Algorithm 7

Research on Image Edge Detection Method Based on Wolf King A...

引用

7th ieee international conference on Information systems and Computer Aided Education, ICISCAE 2024

作者： Jian, Chang Yimeng, Fan School of Software Liaoning Technical University Huludao125105 China

ISBN: (纸本)9798350350760

Aiming at the problem that the current image edge detection algorithm is not accurate enough to capture the edge contour, an image edge detection algorithm based on Wolf king algorithm was proposed. Firstly, local principal component analysis and generalized Gaussian prior were used to improve the Gaussian filter, so that the image noise was effectively suppressed and the detail information was significantly enhanced. Secondly, multi-direction gradient calculation is proposed to reduce the influence of noise on gradient estimation and provide more information to locate the edge, so as to determine the position and direction of the edge more accurately. Finally, the Wolf king algorithm proposed in this paper is based on the grey Wolf algorithm, which is improved by using the nonlinear convergence factor and adaptive weight strategy. The improved algorithm is used to optimize Otsu to obtain the image threshold, realize the automatic acquisition of the image high and low threshold, and further improve the accuracy of the algorithm. More detailed edge contour information can be extracted from the image processed by the above method. The experimental results show that the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) of the images processed by the LPG-PCA image denoising algorithm are increased by 18.8% and 13.6% respectively compared with the traditional Gaussian filtering. In terms of threshold processing, compared with most existing edge detection algorithms, the Wolf king algorithm proposed in this paper can accurately detect the edge contour, and it is more coherent in edge extraction, with better unilateral response effect and better algorithm performance. ©2024 ieee.

关键词： Wiener filtering

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BEIG-SOLO: A Binary Edge image Guidance based Aircraft image Instance Segmentation Network 17

BEIG-SOLO: A Binary Edge Image Guidance based Aircraft Image...

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17th ieee international conference on signal Processing, ICSP 2024

作者： Li, Yanshan Wen, Yamin Li, Wei Shenzhen University College of Electronics and Information Engineering Shenzhen China

ISBN: (纸本)9798350387384

With the continuous advancement of aviation and sensor technology, aircraft image instance segmentation technology is becoming increasingly important in the military and civilian fields. Due to the characteristics of small intra-class similarity and large inter-class similarity of aircraft in aircraft images, as well as the influence of its shooting conditions and complex background, it is difficult for the existing aircraft image instance segmentation technology to segment aircraft images accurately and difficult separating targets from barrier and complex backgrounds. Therefore, how to accurately segment aircraft images based on their characteristics and improve the model's robustness to occlusion, illumination, and viewing angle changes has become the focus of recent research. In response to the above challenges, we propose an aircraft image instance segmentation network based on binary edge image guidance (BEIG-SOLO). By adding a binary edge image guidance module and minimum cost allocation, the proposed network performs well in the aircraft image instance segmentation task, with advanced performance. First, we built a binary edge image guidance module (BEIGM), which combines the feature information of binary edge images and aircraft images, including a binary edge image information extraction module, top-down and bottom-up fusion module, and embedded into the output of the feature extraction network to enhance the network's perception of the boundary feature information of the aircraft image. Secondly, we propose a positive and negative sample labelling strategy based on minimum cost allocation (MCA), which can calculate the sum of the classification and segmentation costs of all grids and mark the grid with the most minor combined cost as a positive sample to solve multiple Poor segmentation problem caused by overlapping aircraft instance objects. Finally, experimental results on the actual aircraft image and COCO dataset demonstrate our model's advanced perfo

关键词： image segmentation

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Bearing Fault image Recognition in Strong Noise based on Optimized CNN Architecture 2

Bearing Fault Image Recognition in Strong Noise Based on Opt...

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2nd ieee international conference on image Processing and Computer Applications, ICIPCA 2024

作者： Li, Qiang Gai, Haowen Hu, Kaijie Northeastern University Shenyang China Tianjin College University of Science and Technology Beijing Tianjin China Zhonghuan Information College Tianjin University of Technology Tianjin China

ISBN: (纸本)9798350360240

To address the problem of low accuracy and poor stability of bearing diagnostic models under strong background noise, a bearing fault image recognition method is proposed that reduces the randomness of the model by avoiding the need for artificial parameterization, which can introduce random factors. This method is based on hyperparameter optimization of the GoogLeNet convolutional neural network model and decision fusion. First of all, two-dimensional wavelet time-frequency variation of the original signal of the bearing vibration to construct an image dataset, one-dimensional classification is into a two-dimensional image problem;Secondly, three lightweight convolutional neural network architectures are selected for the noise immunity test, to get the best noise-resistant network architecture GoogLeNet;Finally, hyper-parameter optimization is performed for the network, comparing the mesh method, the progressive mesh method, and the group optimization algorithm, respectively, and getting The optimal parameters are then analyzed for decision fusion and visualization of the network. To verify the method proposed in this paper, we used the open Case Western Reserve University bearing dataset. The experimental verification demonstrates that the proposed method achieves a correctness rate of 94.33% in decision fusion under noise, with good accuracy and stability. © 2024 ieee.

关键词： Mesh generation

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