Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470681
Liang Zhang, Yuan Fang, Yuexin Shen, Xiyin Wang
With the rapid development of information technology, the problem of network security has become increasingly prominent. Camouflage intrusion, as a common means of network attack, has strong concealment and destructiveness, which brings great security threats to enterprises and organizations. In order to effectively deal with camouflage intrusion, more and more researchers apply machine learning and data mining technology to the field of intrusion detection. Among them, Random Forest (RF) algorithm, as an ensemble learning algorithm, has the advantages of high accuracy and low complexity, and has been widely concerned. However, the traditional RF algorithm still has some problems when dealing with camouflage intrusion detection, such as single feature selection, strong correlation between base classifiers and so on
{"title":"Research on Smart Contract Vulnerability Detection Method of Power Equipment Based on Deep Learning Algorithm","authors":"Liang Zhang, Yuan Fang, Yuexin Shen, Xiyin Wang","doi":"10.1109/ICOCWC60930.2024.10470681","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470681","url":null,"abstract":"With the rapid development of information technology, the problem of network security has become increasingly prominent. Camouflage intrusion, as a common means of network attack, has strong concealment and destructiveness, which brings great security threats to enterprises and organizations. In order to effectively deal with camouflage intrusion, more and more researchers apply machine learning and data mining technology to the field of intrusion detection. Among them, Random Forest (RF) algorithm, as an ensemble learning algorithm, has the advantages of high accuracy and low complexity, and has been widely concerned. However, the traditional RF algorithm still has some problems when dealing with camouflage intrusion detection, such as single feature selection, strong correlation between base classifiers and so on","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"52 3","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529904","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470477
Deepak Kumar, Febin Prakash, Gaurav Shukla
this paper investigates the antenna-to-antenna spatial correlation of a multi-consumer millimeter-wave (mm Wave) system, considering the angular spread of every randomly located antenna inside the mobile. A signal-power-dependent correlation model based on the azimuth perspective domain is proposed. Furthermore, an iterative clustering set of rules for unmarried-cellular beam forming is advanced and analyzed to quantify the performance of multi-user mm Wave structures. Simulation outcomes show that after the angular spread exceeds 20°, the antenna-to-antenna correlation must be considered within the analysis. The beam forming overall performance with antenna correlation substantially progresses with a reduction in the number of antennas, and the benefit increases because the angular spread increases.
{"title":"Analysis of Antenna-to-Antenna Spatial Correlation in Multi-User Millimeter-Wave Systems","authors":"Deepak Kumar, Febin Prakash, Gaurav Shukla","doi":"10.1109/ICOCWC60930.2024.10470477","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470477","url":null,"abstract":"this paper investigates the antenna-to-antenna spatial correlation of a multi-consumer millimeter-wave (mm Wave) system, considering the angular spread of every randomly located antenna inside the mobile. A signal-power-dependent correlation model based on the azimuth perspective domain is proposed. Furthermore, an iterative clustering set of rules for unmarried-cellular beam forming is advanced and analyzed to quantify the performance of multi-user mm Wave structures. Simulation outcomes show that after the angular spread exceeds 20°, the antenna-to-antenna correlation must be considered within the analysis. The beam forming overall performance with antenna correlation substantially progresses with a reduction in the number of antennas, and the benefit increases because the angular spread increases.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"51 12","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470666
G. D, Ramakant Upadhyay, Ashendra Kumar Saxena
the overall performance of satellite communication links is extraordinarily established upon the spatial distribution of transmitted radiation. This distribution is managed by means of the antenna beam sample, which is a measure of the relative power emitted in one-of-a-kind directions from the antenna. The shape of the beam drastically impacts the efficiency of the hyperlink in addition to its robustness against fading. Numerous beam sample configurations are typically employed in satellite verbal exchange packages; every with it's set of advantages and disadvantages. By characterizing the variations among beam patterns, it is miles feasible to determine the most suitable design for a given utility. The most commonly used beam sample in satellite TV for PC communications is the pencil beam. This has a highly slim fundamental lobe width and presents exact gain traits inside the desired guidelines on the fee of extended aspect lobe power. This may cause better interference levels and fading outcomes, in particular in tremendously Asymmetric Circularly Polarized (HACP) structures. Then again, wider beam styles, which include fan or zone beams, provide decreased aspect lobe electricity on the fee of reduced gain. Broadening the sample will additionally increase the complexity of the link finances and antenna directivity calculations. Currently, extra complex antenna beam styles, including stepped-tapered, nested, and adaptive, have been hired so one can optimize the satellite TV for PC link overall performance.
卫星通信链路的整体性能主要取决于传输辐射的空间分布。这种分布是通过天线波束样本来管理的，波束样本是对天线在特定方向上发射的相对功率的测量。波束的形状会极大地影响超链接的效率和抗衰减能力。卫星语言交换软件包中通常会采用多种波束样态配置，每种配置都有各自的优缺点。通过分析波束模式之间的变化，可以确定最适合特定用途的设计。在用于 PC 通信的卫星电视中，最常用的波束样品是铅笔波束。这种波束具有非常纤细的基本波束宽度，并能在所需的准则范围内呈现精确的增益特性，但要以扩展边叶功率为代价。这可能会导致更好的干扰水平和衰减结果，尤其是在极大不对称圆极化（HACP）结构中。另外，更宽的波束样式，包括扇形波束或区域波束，会以降低增益为代价减少边叶功率。拓宽样本还会增加链路财务和天线指向性计算的复杂性。目前，人们已经采用了更复杂的天线波束样式，包括阶梯锥形、嵌套和自适应，从而可以优化 PC 链路的卫星电视整体性能。
{"title":"Impact of Antenna Beam Patterns on the Performance of Satellite Communication Links","authors":"G. D, Ramakant Upadhyay, Ashendra Kumar Saxena","doi":"10.1109/ICOCWC60930.2024.10470666","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470666","url":null,"abstract":"the overall performance of satellite communication links is extraordinarily established upon the spatial distribution of transmitted radiation. This distribution is managed by means of the antenna beam sample, which is a measure of the relative power emitted in one-of-a-kind directions from the antenna. The shape of the beam drastically impacts the efficiency of the hyperlink in addition to its robustness against fading. Numerous beam sample configurations are typically employed in satellite verbal exchange packages; every with it's set of advantages and disadvantages. By characterizing the variations among beam patterns, it is miles feasible to determine the most suitable design for a given utility. The most commonly used beam sample in satellite TV for PC communications is the pencil beam. This has a highly slim fundamental lobe width and presents exact gain traits inside the desired guidelines on the fee of extended aspect lobe power. This may cause better interference levels and fading outcomes, in particular in tremendously Asymmetric Circularly Polarized (HACP) structures. Then again, wider beam styles, which include fan or zone beams, provide decreased aspect lobe electricity on the fee of reduced gain. Broadening the sample will additionally increase the complexity of the link finances and antenna directivity calculations. Currently, extra complex antenna beam styles, including stepped-tapered, nested, and adaptive, have been hired so one can optimize the satellite TV for PC link overall performance.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"37 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470708
Zirui Feng
Image processing technology is an important branch in the digital age, and its application in art design has penetrated into various fields. Whether it is graphic design, three-dimensional modeling, or film and television special effects, image processing technology provides artists and designers with unprecedented creative possibilities. This paper will deeply analyze the image processing technology, and discuss its application and challenges in art design.
{"title":"Design and Implementation of Art Design System based on Image Processing Technology","authors":"Zirui Feng","doi":"10.1109/ICOCWC60930.2024.10470708","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470708","url":null,"abstract":"Image processing technology is an important branch in the digital age, and its application in art design has penetrated into various fields. Whether it is graphic design, three-dimensional modeling, or film and television special effects, image processing technology provides artists and designers with unprecedented creative possibilities. This paper will deeply analyze the image processing technology, and discuss its application and challenges in art design.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"47 5","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470928
Bowei Xing, Yin He, Chi Xu, Yong Zhang
Facing the complex electromagnetic environment, the modulation mode of communication signal is becoming increasingly complex. The existing detection methods of modulation mode of communication signal can not detect the modulation mode of communication signal accurately and quickly. In order to facilitate the presentation, we represent the digital signal on the complex plane, form the constellation map according to the mapping formula, analyze the difference of the characteristics of the constellation map, and train and test the constellation map. It can be found that when the signal-to-noise ratio is lower than 20dB, the classification accuracy of the characteristics of the constellation map is greatly affected for the 64QAM signal with the largest number of points and the smallest radius. To solve this problem, A method of signal constellation de-noising using VMD is proposed. Compared with the pre-de-noising method, the average accuracy of VGGNet-16 classification is increased by 7.76%; The average accuracy rate of ResNet-18 classification increased by 9.77%; The average accuracy rate of ResNet-50 classification increased by 7.57%. This method improves the accuracy of constellation classification detection, which is difficult to improve, and lays a good foundation for the research of modulation signal detection methods.
{"title":"Research on Modulation Signal Detection Method based on Deep Learning","authors":"Bowei Xing, Yin He, Chi Xu, Yong Zhang","doi":"10.1109/ICOCWC60930.2024.10470928","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470928","url":null,"abstract":"Facing the complex electromagnetic environment, the modulation mode of communication signal is becoming increasingly complex. The existing detection methods of modulation mode of communication signal can not detect the modulation mode of communication signal accurately and quickly. In order to facilitate the presentation, we represent the digital signal on the complex plane, form the constellation map according to the mapping formula, analyze the difference of the characteristics of the constellation map, and train and test the constellation map. It can be found that when the signal-to-noise ratio is lower than 20dB, the classification accuracy of the characteristics of the constellation map is greatly affected for the 64QAM signal with the largest number of points and the smallest radius. To solve this problem, A method of signal constellation de-noising using VMD is proposed. Compared with the pre-de-noising method, the average accuracy of VGGNet-16 classification is increased by 7.76%; The average accuracy rate of ResNet-18 classification increased by 9.77%; The average accuracy rate of ResNet-50 classification increased by 7.57%. This method improves the accuracy of constellation classification detection, which is difficult to improve, and lays a good foundation for the research of modulation signal detection methods.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"39 11","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470537
Rakhi Gupta, Gaurav Kumar Rajput, M. N. Nachappa
This paper provides a unique low electricity facts aggregation method utilizing the Extended Kalman Filtering (EKF) algorithm. Using time-collection evaluation on low energy facts streams, EKF can provide extra correct mixture values. This paper examines the system of characteristic extraction from low-strength records series streams and the underlying prolonged Kalman Filtering (EKF) model formula. The EKF version formula produces a correlated time-series representation of the low-strength records streams and estimates its parameters. Further, a case study of the real-world utility of this technique is supplied. The outcomes show that the proposed methodology can yield an advanced low-energy records aggregation method compared to standard strategies. The proposed EKF -based method holds the giant capacity for efficient strength, calling for forecasting in realistic settings. This paper examines prolonged Kalman Filtering (EKF) for low electricity information aggregation of time series evaluation. EKF is a recursive estimation technique primarily based on first principles and implements an optimally weighted linear aggregate of recursive estimates for nations and parameters. This look presents the analytical method of EKF implemented for the cause of time collection modeling and state estimation. A simulated case look at on-strength demand for a given length illustrates the gain of EKF for the low-strength data aggregation venture., a correct estimation is obtained from the time series information with a restrained range of samples and minimum computational attempt.
{"title":"Time Series Analysis for Low Energy Data Aggregation Using Extended Kalman Filtering","authors":"Rakhi Gupta, Gaurav Kumar Rajput, M. N. Nachappa","doi":"10.1109/ICOCWC60930.2024.10470537","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470537","url":null,"abstract":"This paper provides a unique low electricity facts aggregation method utilizing the Extended Kalman Filtering (EKF) algorithm. Using time-collection evaluation on low energy facts streams, EKF can provide extra correct mixture values. This paper examines the system of characteristic extraction from low-strength records series streams and the underlying prolonged Kalman Filtering (EKF) model formula. The EKF version formula produces a correlated time-series representation of the low-strength records streams and estimates its parameters. Further, a case study of the real-world utility of this technique is supplied. The outcomes show that the proposed methodology can yield an advanced low-energy records aggregation method compared to standard strategies. The proposed EKF -based method holds the giant capacity for efficient strength, calling for forecasting in realistic settings. This paper examines prolonged Kalman Filtering (EKF) for low electricity information aggregation of time series evaluation. EKF is a recursive estimation technique primarily based on first principles and implements an optimally weighted linear aggregate of recursive estimates for nations and parameters. This look presents the analytical method of EKF implemented for the cause of time collection modeling and state estimation. A simulated case look at on-strength demand for a given length illustrates the gain of EKF for the low-strength data aggregation venture., a correct estimation is obtained from the time series information with a restrained range of samples and minimum computational attempt.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"14 6","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470613
Associate Professor A Kannagi, Neeraj Das, Meenakshi Dheer
in excessive-performance computing environments, wherein huge amounts of data want to be processed quickly, the overall performance of statistics processing systems is crucial. Analyzing the performance of these structures is essential to become aware of bottlenecks and optimize their performance. This studies aims to increase statistical strategies for overall performance analysis of facts processing systems in high-performance computing environments. The evaluation technique is to gather overall performance facts from the goal device. This fact frequently consists of numerous measurements, making it challenging to draw meaningful insights. To cope with this difficulty, statistical strategies, transformation, outlier detection, and dimensionality discount can be implemented to clear out noise and pick out styles within the records. Regression evaluation may version the relationship among gadget parameters and overall performance metrics. It helps identify which device parameters have the most considerable effect on performance and may guide similarly optimization efforts. Moreover, cluster analysis can be used to institution systems with comparable performance traits, allowing comparison and identity of pinnacle-appearing systems.
{"title":"Statistical Methods for Performance Analysis of Data Processing Systems in High-Performance Computing Environments","authors":"Associate Professor A Kannagi, Neeraj Das, Meenakshi Dheer","doi":"10.1109/ICOCWC60930.2024.10470613","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470613","url":null,"abstract":"in excessive-performance computing environments, wherein huge amounts of data want to be processed quickly, the overall performance of statistics processing systems is crucial. Analyzing the performance of these structures is essential to become aware of bottlenecks and optimize their performance. This studies aims to increase statistical strategies for overall performance analysis of facts processing systems in high-performance computing environments. The evaluation technique is to gather overall performance facts from the goal device. This fact frequently consists of numerous measurements, making it challenging to draw meaningful insights. To cope with this difficulty, statistical strategies, transformation, outlier detection, and dimensionality discount can be implemented to clear out noise and pick out styles within the records. Regression evaluation may version the relationship among gadget parameters and overall performance metrics. It helps identify which device parameters have the most considerable effect on performance and may guide similarly optimization efforts. Moreover, cluster analysis can be used to institution systems with comparable performance traits, allowing comparison and identity of pinnacle-appearing systems.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"46 34","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470710
Surendra Yadav, Rakesh Kumar Dwivedi, Gobi N
this study appears to use self-supervised transfer mastering for sturdy scientific photo classes. Switch getting to know is a powerful approach for enhancing the accuracy of deep mastering fashions in scientific imaging. This paper investigates using self-supervised getting-to-know techniques for scientific picture classes within characteristic-based procedures. By leveraging self-supervised schooling strategies, consisting of contrastive mastering, distributed representations, clustering, pseudo-venture gaining knowledge of, and self-supervised multi-undertaking gaining knowledge of, the proposed technique can learn representations that are extra sturdy to the area shift of various clinical imaging datasets. Experiments performed on an extensive x-ray and ultrasound snapshots dataset reveal that the proposed approach affords extra improvement in type accuracy compared to traditional feature-primarily based techniques.
这项研究似乎将自监督转移掌握用于坚固的科学照片类。在科学成像中，转换获取知识是提高深度掌握方法准确性的有力方法。本文研究了在基于特征的程序中对科学图片类别使用自监督获取知识技术。通过利用自监督学习策略（包括对比掌握、分布式表示、聚类、伪探险获取知识和自监督多目标获取知识），所提出的技术可以学习到对各种临床成像数据集的区域变化更坚固的表示。在一个广泛的 X 射线和超声波快照数据集上进行的实验表明，与传统的基于特征的技术相比，所提出的方法能进一步提高类型准确性。
{"title":"Leveraging Self-Supervised Transfer Learning for Robust Medical Image Classification","authors":"Surendra Yadav, Rakesh Kumar Dwivedi, Gobi N","doi":"10.1109/ICOCWC60930.2024.10470710","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470710","url":null,"abstract":"this study appears to use self-supervised transfer mastering for sturdy scientific photo classes. Switch getting to know is a powerful approach for enhancing the accuracy of deep mastering fashions in scientific imaging. This paper investigates using self-supervised getting-to-know techniques for scientific picture classes within characteristic-based procedures. By leveraging self-supervised schooling strategies, consisting of contrastive mastering, distributed representations, clustering, pseudo-venture gaining knowledge of, and self-supervised multi-undertaking gaining knowledge of, the proposed technique can learn representations that are extra sturdy to the area shift of various clinical imaging datasets. Experiments performed on an extensive x-ray and ultrasound snapshots dataset reveal that the proposed approach affords extra improvement in type accuracy compared to traditional feature-primarily based techniques.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"20 13","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470883
Febin Prakash, Sachin Gupta, Garima Goswami
The objective of the modern-day work is to propose a characteristic extraction of the usage of canonical correlation analysis (CCA) mixed with different advanced strategies for the advanced recognition of items in hyperspectral data. CCA has come to be a famous tool for characteristic extraction as it permits nonlinear modeling of the information that's, in particular, helpful while we are exposing a hyperspectral photograph. CCA seeks to maximize the correlation between variable sets which is especially useful when the image consists of spurious noise, which might otherwise degrade the overall recognition performance. Additionally, CCA allows for retaining the spatial patterns inside the information. Other preprocessing and statistical techniques such as wavelet transforms, statistical covariance illustration, Kreskas-Wallis, and second Estimation strategies have been integrated into this work to improve the effects further. Experimental outcomes demonstrate that the proposed technique based totally on CCA, while combined with different techniques, improves the recognition rate of items and offers a better fitting of the information.
这项现代研究的目标是提出一种特征提取方法，利用典型相关分析（CCA）与不同的高级策略相结合，对高光谱数据中的项目进行高级识别。CCA 已成为特征提取的著名工具，因为它允许对信息进行非线性建模，这在我们曝光高光谱照片时尤其有用。CCA 致力于最大限度地提高变量集之间的相关性，这在图像包含杂散噪声时尤其有用，否则可能会降低整体识别性能。此外，CCA 还能保留信息中的空间模式。其他预处理和统计技术，如小波变换、统计协方差图解、Kreskas-Wallis 和二次估计策略，也被整合到这项工作中，以进一步提高效果。实验结果表明，所提出的完全基于 CCA 的技术与不同的技术相结合，提高了项目的识别率，并提供了更好的信息拟合。
{"title":"Feature Extraction Using Canonical Correlation Analysis for Improved Recognition of Objects in Hyper Spectral Data","authors":"Febin Prakash, Sachin Gupta, Garima Goswami","doi":"10.1109/ICOCWC60930.2024.10470883","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470883","url":null,"abstract":"The objective of the modern-day work is to propose a characteristic extraction of the usage of canonical correlation analysis (CCA) mixed with different advanced strategies for the advanced recognition of items in hyperspectral data. CCA has come to be a famous tool for characteristic extraction as it permits nonlinear modeling of the information that's, in particular, helpful while we are exposing a hyperspectral photograph. CCA seeks to maximize the correlation between variable sets which is especially useful when the image consists of spurious noise, which might otherwise degrade the overall recognition performance. Additionally, CCA allows for retaining the spatial patterns inside the information. Other preprocessing and statistical techniques such as wavelet transforms, statistical covariance illustration, Kreskas-Wallis, and second Estimation strategies have been integrated into this work to improve the effects further. Experimental outcomes demonstrate that the proposed technique based totally on CCA, while combined with different techniques, improves the recognition rate of items and offers a better fitting of the information.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"56 52","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140529617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.1109/ICOCWC60930.2024.10470551
Feon Jaison, Viiay Kumar Pandey, Ashish Bishnoi
help vector machines (SVMs) have become increasingly famous in scientific photo analysis because of their capacity to model complex relationships among inputs and outputs. SVMs are exceptionally high-quality because of their advanced overall performance in excessive-dimensional information units and their ability to address non-linear information. In clinical image evaluation, SVMs are used for various packages, including detecting tumors in Magnetic Resonance Imaging (MRI) and classifying lesions in Computed Tomography (CT) scans. No matter its benefits, growing dependable SVMs for scientific photograph evaluation remains a venture because of the uncertainty associated with scientific pics that regularly require information preprocessing and feature extraction before education. This paper surveys current work on developing robust SVMs for medical photo analysis, from preprocessing to publish-processing, and affords a comprehensive evaluation of the cutting-edge state of the art. mainly; we discuss diverse preprocessing and function extraction strategies that can be employed to improve performance, in addition to publish-processing strategies that can be used to enhance the general accuracy of the version. We also talk about ability directions for future research in this field.
{"title":"Developing Support Vector Machines for Accurate Medical Image Analysis","authors":"Feon Jaison, Viiay Kumar Pandey, Ashish Bishnoi","doi":"10.1109/ICOCWC60930.2024.10470551","DOIUrl":"https://doi.org/10.1109/ICOCWC60930.2024.10470551","url":null,"abstract":"help vector machines (SVMs) have become increasingly famous in scientific photo analysis because of their capacity to model complex relationships among inputs and outputs. SVMs are exceptionally high-quality because of their advanced overall performance in excessive-dimensional information units and their ability to address non-linear information. In clinical image evaluation, SVMs are used for various packages, including detecting tumors in Magnetic Resonance Imaging (MRI) and classifying lesions in Computed Tomography (CT) scans. No matter its benefits, growing dependable SVMs for scientific photograph evaluation remains a venture because of the uncertainty associated with scientific pics that regularly require information preprocessing and feature extraction before education. This paper surveys current work on developing robust SVMs for medical photo analysis, from preprocessing to publish-processing, and affords a comprehensive evaluation of the cutting-edge state of the art. mainly; we discuss diverse preprocessing and function extraction strategies that can be employed to improve performance, in addition to publish-processing strategies that can be used to enhance the general accuracy of the version. We also talk about ability directions for future research in this field.","PeriodicalId":518901,"journal":{"name":"2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC)","volume":"25 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140530009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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