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A New Elimination Based Multi-Material Reconstruction for Spectral CT Imaging 3

A New Elimination Based Multi-Material Reconstruction for Sp...

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3rd international conference on Optics and Image processing, ICOIP 2023

作者： Yu, Xiaohuan Cai, Ailong Li, Lei Yan, Bin Henan Key Laboratory of Imaging and Intelligent Processing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (纸本)9781510667426

Spectral computed tomography (spectral CT) is an emerging imaging technology that is capable of distinguishing material properties. However, the difficulty of decomposition process is intensified by the nonlinearity of the measurements and ill-conditioned problem, particularly when the number of materials and energies do not match. Therefore, the key issue in spectral CT is to design an improved algorithm in the accurate material decomposition. This study proposes a one-step multi-material algorithm that combines a statistical reconstruction model with a gradient-sparsity based prior. In our approach, the elimination based method under volume conservation constrained condition is designed for the inconsistent scanning of number of materials and energies. Newton descent method is adopted to efficiently solve the optimization problem based on a simple surrogate function. Through simulated experiments, the proposed method achieves a significantly higher peak signal-to-noise ratio (PSNR) compared to other algorithms, with an increase of approximately 23.988 dB and 23.462 dB. Numerical experiments have confirmed the efficiency of our proposed method in reconstructing the material distributions while reducing noise compared to state-of-the-art methods. © 2023 SPIE. All rights reserved.

关键词： signal to noise ratio

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Research on Image Art Creation System of Integrated 3D Computer Image Vision Digital Media 3

Research on Image Art Creation System of Integrated 3D Compu...

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3rd IEEE international conference on Electrical Engineering, Big data and Algorithms, EEBDA 2024

作者： Liu, Yang Guo, Dongqi Institute of Arts and Media Guangzhou Vocational University of Science and Technology Guangzhou China Jeonbuk National University Department of Industrial Design Jeonju Korea Republic of

ISBN: (纸本)9798350380989

The accuracy and real-time performance of existing image labeling algorithms are not high. This project intends to study the video sequence feature labeling algorithm for digital multimedia images. A digital multimedia image segmentation method based on wavelet transform is proposed. Then the system adopts the color video segmentation method based on edge detection. Based on visual salience features, the model combines color features and gradient features to describe local image quality. The method fuses the brightness channels of the reference image and the corresponding distorted image, and calculates the similarity between the gradient map of the channel and the gradient map of the reference/distorted image. Target detection is realized by matching the target image with the gray information. Then the color feature and gradient feature are combined organically by means of the mean offset weight method, and a better image quality evaluation effect is obtained. The performance of many evaluation algorithms and has some advantages compared with the existing evaluation methods. © 2024 IEEE.

关键词： 3D image recognition media image digital processing visual feature

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Spectral data Migration of Seawater COD Using Generative Adversarial Networks to Address Differences in Spectral Features and Insufficient Samples Across Regions 3

Spectral Data Migration of Seawater COD Using Generative Adv...

引用

3rd international conference on Electronic Information Engineering and Computer Science, EIECS 2023

作者： Hou, Shiwei Zhang, Yingying Yuan, Da Feng, Xiandong Institute of Oceanographic Instrumentation Shandong Provincial Key Laboratory of Ocean Environmental Monitoring Technology Qingdao China

ISBN: (纸本)9798350316674

Chemical oxygen demand (COD) is an indicator of organic matter content in water, and its sensitive spectral regions depend on the species and concentrations of organics present. In recent years, spectroscopic analysis methods using feature variable modeling have become important for seawater COD detection. However, due to differences in COD compositions across regions and insufficient single-region samples, issues like varying spectral features and inadequate samples make data processing with deep learning difficult. To address this, we propose a seawater COD spectral data migration method using generative adversarial networks, aiming to resolve problems caused by varying COD compositions and insufficient samples across regions. Our method employs WGAN-GP for network training to achieve spectral data migration between regions. The improved WGAN-GP generator produces simulated data highly similar to real data, thereby enabling COD spectral data migration. This method can effectively address issues of varying spectral features and inadequate samples across regions, improving the accuracy and reliability of seawater COD spectral data analysis. © 2023 IEEE.

关键词： Generative Adversarial Networks Seawater COD Spectral data Migration Varying Spectral Features

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data Clustering Approach on the Basis of data Sensitivity for Implementation of Secure Cloud Computing Environment 3rd

Data Clustering Approach on the Basis of Data Sensitivity fo...

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3rd international conference on Machine Learning, Image processing, Network Security and data Sciences, MIND 2021

作者： Singh, Rajdeep Pateriya, R.K. Department of Computer Science & Engineering Mewar University Rajasthan Chittorgarh India

ISBN: (纸本)9789811958670

In the work illustrated, an effective approach has been proposed for handling data for the cloud computing environment. Here, the sensitivity of data is derived from data weights that in turn based on the size of the file and attribute scale for the preprocessing. The categorization of the sensitivity is based on the 10 attributes, and it has been selected on the basis of the size and information of data. Afterward, for clustering of similar elements, K-means clustering algorithm is applied which clusters the data in maximum of 5 clusters. It is been used to perform data sensitivity analysis and encryption. In terms of data categorization and processing in a cloud computing environment, the approach demonstrates its efficacy. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cloud security

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Design and realization of a 6-rod 1-DOF robot 3

Design and realization of a 6-rod 1-DOF robot

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3rd international conference on Advanced Manufacturing Technology and Manufacturing Systems, ICAMTMS 2024

作者： Wang, Zihang Shen, Jiaxu Liu, Jiacheng Tian, Bo Hu, Liyong Lou, Junqiang Ningbo University Zhejiang Ningbo315000 China NingboTech University Zhejiang Ningbo315000 China

ISBN: (纸本)9781510681804

This paper proposes a millimeter-scale microrobot, which can be used for MIS (minimally invasive surgery) to achieve the 1-DOF (single degree of freedom) motion. The mechanism is driven by piezo-bimorphs, and the voltage is eventually converted into displacement. The dragonfly-like flapping wing amplification mechanism is adopted, which has characteristics of high precision, small size and excellent dynamic performance. In this paper, the kinematic mode of the structure is analyzed first, then the manufacturing process and processing method of the microrobot are introduced. The microrobot achieve a dimension of 22×22×23mm (excluding piezo-bimorph). Finally, open-loop experiment is conducted on the tracking performances of the microrobot by repeatedly following the vertical line trajectory. The horizontal motion range is 2.05mm, and the straightness in the stroke is 99.14%. Also, the RMS (root-mean-square) accuracy of the linear trajectory is 8.38±0.3μm. These show the high positioning accuracy and effective tracking ability of the microrobot. © 2024 SPIE.

关键词： Design Epoxies Manufacturing signal processing Surgery Kinematics Laser cutting Polyimides

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Bangladeshi Fresh-Rotten Fruit & Vegetable Detection Using Deep Learning Deployment in Effective Application 3

Bangladeshi Fresh-Rotten Fruit & Vegetable Detection Using D...

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3rd IEEE international conference on Computer Communication and Artificial Intelligence, CCAI 2023

作者： Hamim, Md Abrar Tahseen, Jeba Hossain, Kazi Md. Istiyak Akter, Nasrin Asha, Umme Fatema Tuj Daffodil International University Department of Computer Science Dhaka Bangladesh

ISBN: (纸本)9798350335262

Finding rotten fruits and vegetables has been important, especially in the agricultural industry. Computer vision has significant applications in the automation of damaged, freshness detection of fruits and vegetables. In recent decades, the farming sector has discovered computer machine vision and image processing technology to be more and more beneficial, particularly for implementations in quality control by identifying rotten and freshness. Farmers cannot contribute effectively between fresh and rotten fruits, vegetables because this is mainly done by people. People tire out after performing the same task for several days, whereas robots do not. By identifying weaknesses in agricultural product, the study suggested a technique for minimizing human effort and worktime. Vegetables and fruits with defects might affect healthy fruits if they are not identified in time. As an outcome, we put up a methodology to stop rottenness from spreading. The suggested model detects between fresh and decaying fruits and vegetables depending on the input fruit and vegetable photos. In this work, we used six different types of fruits and vegetables like carrot, potato, calabash, cucumber, eggplant, and cauliflower, as well as fruits likes mango, banana, star fruit, jackfruit, guava, and papaya. This study discusses multiple image processing methods for rottenness categorization of fruits and vegetables. A Convolutional Neural Network (CNN), KNN, and SVM are used to gather the features from the data fruit and vegetable photos. On Google and Kaggle datasets, the efficiency of the suggested model is evaluated, and CNN model shows the greatest accuracy which is 95 percent. © 2023 IEEE.

关键词： Vegetables

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CDCCA-RPPGFormer: Transformer-Like Network Based on 3D-CDC-ST and ECA for Remote Heart Rate Measurement 3

CDCCA-RPPGFormer: Transformer-Like Network Based on 3D-CDC-S...

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3rd IEEE international conference on Information Technology, Big data and Artificial Intelligence, ICIBA 2023

作者： Ma, Xiaolin Wang, Zhaosen Kuang, Hailan Liu, Xinhua Wuhan University of Technology School of Information Engineering Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan430070 China

ISBN: (纸本)9781665490788

Remote heart rate measurement methods based on remote photoplethysmography (rPPG) signals can be divided into traditional methods, convolutional neural network (CNN) based methods, and visual transformer based methods. However, the majority of visual transformer based methods are based on multihead self-attention mechanism whose computational complexity grows quadratically with the increase in video resolution and time, impeding their deployment and application on terminal devices, particularly mobile devices. To address this issue, this paper proposes a transformer-like network named CDCCA-RPPGFormer for remote heart rate measurement. The combination of 3D spatio-temporal central difference convolution (3D-CDC-ST) and 3D efficient channel attention (ECA) convolution is used to replace the multi-head attention mechanism in the traditional transformer, which can effectively extract the rPPG signal features, focus the model on useful features, reduce noise interference, and reduce computational complexity. Afterward, the model is given the ability to accurately recover the rPPG signal by utilizing precise supervision from both the time and frequency domains. Our model achieved the lowest MAE, RMSE, and highest Pearson's correlation coefficient (r) in both experiments on the UBFC-rPPG and PURE datasets. Compared to the CDCA-rPPGNet method using the same preprocessing method, the CDCCA-RPPGFormer method decreases MAE and RMSE by 13.3% and 8.7% on the UBFC dataset and by 10.9% and 26.7% on the PURE dataset. Meanwhile, the CDCCA-RPPGFormer method reduces MAE and RMSE on the PURE dataset by 62.7% and 62.3%, respectively, compared to the visual transformer based Physformer method. These data fully demonstrate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Convolution

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Dark channel a priori defogging algorithm based on a combination of bright channel inversion and dark channel weighting 3

Dark channel a priori defogging algorithm based on a combina...

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3rd international conference on Optics and Image processing, ICOIP 2023

作者： Wei, Qida Zhou, Yunqing School of Information Engineering Zhejiang Ocean University Zhoushan316022 China Department of Physics Key Laboratory of Oceanographic Big Data Mining Application of Zhejiang Province Zhejiang Ocean University Zhoushan316000 China

ISBN: (纸本)9781510667426

The classical traditional dark channel priori algorithm causes colour distortion in bright areas of the sky, snow and other surfaces when processing images, and the overall darkness of the recovered image is complicated, resulting in slow processing speed. In this paper, we propose an adaptive modified dark channel priori defogging algorithm that combines inverse bright channel and dark channel weighting. Firstly, the brightest channel of the RGB channel of the fogged image is inverted, and then the dark channel is weighted and combined with the dark channel to correct the dark channel and adaptively correct the transmittance. Secondly, the mean value of the brightest 0.1% of pixels in the new dark channel is used in estimating atmospheric light values;finally, the transmittance estimation is optimised using multi-window fitting and guided filtering methods. Experimental results show that the algorithm improves the dark channel priori colour distortion in bright regions, with faster processing and more effective defogging. © 2023 SPIE. All rights reserved.

关键词： Inverse problems

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Transient extraction from doppler-shifted signal for track-side acoustic bearing fault diagnosis 3

Transient extraction from doppler-shifted signal for track-s...

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3rd international conference on Advanced Algorithms and signal Image processing, AASIP 2023

作者： Liu, Fang Xu, Yifan Zhai, Taotao Liu, Yongbin College of Electrical Engineering and Automation Anhui University Anhui Hefei230601 China National Engineering Laboratory of Energy-Saving Motor and Control Technology Anhui University Hefei230601 China

ISBN: (纸本)9781510668522

One of the main reasons for train derailment is the failure of wheel bearings, and the track-side acoustic detection system (TADS) is one of the effective means to achieve online health monitoring. TADS is based on the basic principle that the acoustic signals emitted by the wheel bearings during the running of the train contain a wealth of diagnostic-related information. The challenge of this technology is how to accurately extract information reflecting the health condition of the wheel bearing from the sound signal. One of the main influence factors is the Doppler effect. To solve this problem, A new "Doppler Single Transient Model (DSTM)"and the "one-by-one stripping"strategy is developed to handle with the periodic fluctuation signal with Doppler distortion in this paper. It consists of three steps: (1) Use the Doppler Periodic Transient Model (DPTM) roughly estimate the parameters of the transient model;(2) The DSTM is used to extract transients from the signal one by one. (3) The optimization algorithms is used to accurately identify parameters. Through the proposed DSTM and the transient extraction strategy, the transients can be matched more accurately. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Doppler effect

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Quick-look method and system for multi-domain space science experiment data 3

Quick-look method and system for multi-domain space science ...

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2023 3rd international conference on Electronic Communication, Computer Science and Technology, ECCST 2023

作者： Yu, Haijun Cao, Kaiyang Yang, Mengbo Li, Shengyang Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences No.9 Dengzhuang South Rd Haidian District Beijing China University of Chinese Academy of Sciences No.1 Yanqihu East Rd Huairou District Beijing China

Space science experiment data contains huge application value. It is important to design methods and systems to have a quick look at the process of data processing. An integration framework is proposed in this paper. Several basic visual components are designed to support the quick look requirements of different types of data. The dynamic configuration mechanism of the visual view can effectively improve the scalability and user experience friendliness of the system. The method of the interactive layout of the front-end interface can make the visual effect of the page richer. It also supports the self-adaptation of the display screen with different resolutions. The dynamic registration mechanism for visual views ensures the synchronization of data display in multiple identical visual views. Finally, a quick-look system is implemented, which achieves the integration and quick look of multi-domain space science experiment data. The validity of the proposed system is verified by the practical application. © Published under licence by IOP Publishing Ltd.

关键词： Dynamics

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