2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)最新文献_第10页

Detection of Glaucoma in Retinal Fundus Images Using Fast Fuzzy C means clustering approach 利用快速模糊C均值聚类方法检测视网膜眼底图像中的青光眼

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974539

Law Kumar Singh, Pooja, H. Garg

引用次数: 7

Face Detection and Recognition Using OpenCV 基于OpenCV的人脸检测与识别

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974493

Maliha Khan, Sudeshna Chakraborty, Rani Astya, Shaveta Khepra

{"title":"Face Detection and Recognition Using OpenCV","authors":"Maliha Khan, Sudeshna Chakraborty, Rani Astya, Shaveta Khepra","doi":"10.1109/ICCCIS48478.2019.8974493","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974493","url":null,"abstract":"Face detection and picture or video recognition is a popular subject of research on biometrics. Face recognition in a real-time setting has an exciting area and a rapidly growing challenge. Framework for the use of face recognition application authentication. This proposes the PCA (Principal Component Analysis) facial recognition system. The key component analysis (PCA) is a statistical method under the broad heading of factor analysis. The aim of the PCA is to reduce the large amount of data storage to the size of the feature space that is required to represent the data economically. The wide 1-D pixel vector made of the 2-D face picture in compact main elements of the space function is designed for facial recognition by the PCA. This is called a projection of self-space. The proper space is determined with the identification of the covariance matrix’s own vectors, which are centered on a collection of fingerprint images. I build a camera-based real-time face recognition system and set an algorithm by developing programming on OpenCV, Haar Cascade, Eigenface, Fisher Face, LBPH, and Python.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115382905","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}

引用次数: 113

Wep, Wap and Wap2 Wireless Network Security Protocol: A Compact Algorithm : (Wireless Network Security Protocol) Wep、Wap和Wap2无线网络安全协议:一种紧凑的算法(无线网络安全协议)

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974517

Abhishek Badholia, Vijayant Verma, S. Kashyap

引用次数: 0

Key enablers influencing the realization of green corridor for the Emergency Vehicles in India using ISM approach 影响印度使用ISM方法实现应急车辆绿色走廊的关键因素

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974516

Zaheeruddin, Hina Gupta

{"title":"Key enablers influencing the realization of green corridor for the Emergency Vehicles in India using ISM approach","authors":"Zaheeruddin, Hina Gupta","doi":"10.1109/ICCCIS48478.2019.8974516","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974516","url":null,"abstract":"The sustainable development of traffic conditions in the urban area is hindered by the improper management of traffic. The characteristics of traffic congestion in the Urban areas vary under the influence of different conditions, such as different day and time of week, count of vehicles on road, causality on road and the parking of vehicles etc. It is necessary to set up the relationships between traffic congestion patterns and those influencing factors, when we conduct macroscopic analysis on the causes of traffic congestion. The bottleneck situation arising out of congestion has made the commuting of Emergency Vehicles(EV) a tedious and tough job. The rationale of this work is to pay heed to the way the Emergency Vehicles commute in order to decline their travel time and provide a clear path. The paper probes into several key issues or key enablers that need to be managed properly in order to have an organised traffic. The work has been carried out on the basis of the previous studies and the discernment of the proficient involved in management of traffic. In this work, a technique named, Interpretive Structure Modelling(ISM) has been employed, for comprehending the hierarchical and contextual affiliation structure amongst the various key enablers.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117197343","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}

引用次数: 0

Machine learning methods for IoT and their Future Applications 物联网的机器学习方法及其未来应用

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974551

A. Rana, Ayodeji Olalekan Salau, Swati Gupta, S. Arora

引用次数: 27

Multimodal Biometric System using Grasshopper Optimization 基于Grasshopper优化的多模态生物识别系统

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974504

Keshav Gupta, G. S. Walia, K. Sharma

引用次数: 5

Autonomic Resource Allocation Frameworks for Service-based Cloud Applications: A Survey 基于服务的云应用的自主资源分配框架:调查

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974463

Reena Panwar, S. M.

引用次数: 3

Blockchain-based Security Solutions to Preserve Data Privacy And Integrity 基于区块链的保护数据隐私和完整性的安全解决方案

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974503

Dev Arora, S. Gautham, H. Gupta, B. Bhushan

引用次数: 21

Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth 干旱植被物种的高光谱数据分析:智能与可持续增长

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974502

S. Borana, S. K. Yadav, S. Parihar

{"title":"Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth","authors":"S. Borana, S. K. Yadav, S. Parihar","doi":"10.1109/ICCCIS48478.2019.8974502","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974502","url":null,"abstract":"Hyperspectral Images are continuous narrow spectral bands provides a wealth of information which can be used in different applications. Advance developments in hyperspectral remote sensing technology since two decade have opened new opportunity to explore innovative ways to study vegetation species. In this research work, ground-based AISA Vis-NIR hyper spectral image system of 240 bands, wavelength range from 390 to 960 nm with 2.5 nm spectral resolution and 1cm spatial resolution at a distance of 10m was used for classification of prominent vegetation species (Cactus, Neem and Babool). Machine learning supervised classification algorithms are used to classifying the Hyperspectral data. In supervised classification, four methods have been used viz. Spectral Angle Mapper (SAM), Minimum Distance (MD), Support Vector Machine (SVM) and Spectral Information Divergence (SID) Classifier. Environment of Visualize Images (ENVI) software is used for processing and analysis of hyperspectral images for classification of vegetation species in Jodhpur study area. Accuracy assessments were also carried out for classified output images and estimate the performance of a classifier. The overall accuracy for SVM classification algorithm is best (81.2%) when 237 hyperspectral bands were used and SAM classification algorithm has provided a better overall accuracy (76.6%) when maximum noise function (MNF) 11 bands were used. This research demonstrated the efficient use of contiguous fine bands of Hyperspectral data in discrimination and classification of vegetation species.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126079215","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}

引用次数: 11

Low Voltage Current Mode Instrumentation Amplifier 低压电流模式仪表放大器

2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2019-10-01 DOI: 10.1109/ICCCIS48478.2019.8974467

D. Agrawal, S. Maheshwari

引用次数: 5