2016 Ninth International Conference on Contemporary Computing (IC3)最新文献_第7页

An efficient automated method for exudates segmentation using image normalization and histogram analysis 一种利用图像归一化和直方图分析的高效自动化渗出物分割方法

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880256

Ashmita Gupta, Ashish Issac, Namita Sengar, M. Dutta

引用次数: 8

Comparative analysis of ELM and No-Prop algorithms ELM算法与No-Prop算法的比较分析

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880217

Abobakr Khalil Alshamiri, Alok Singh, R. Bapi

引用次数: 2

Multiscale image fusion for pansharpening of multispectral images using saliency detection 基于显著性检测的多光谱图像泛锐化多尺度融合

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880253

Shruti, S. Budhiraja

引用次数: 2

Face recognition using Symlet, PCA and cosine angle distance measure 人脸识别使用Symlet, PCA和余弦角距离测量

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880231

Jyotsna, N. Rajpal, V. P. Vishwakarma

{"title":"Face recognition using Symlet, PCA and cosine angle distance measure","authors":"Jyotsna, N. Rajpal, V. P. Vishwakarma","doi":"10.1109/IC3.2016.7880231","DOIUrl":"https://doi.org/10.1109/IC3.2016.7880231","url":null,"abstract":"In this paper an approach for face recognition is proposed using Symlet, PCA and Cosine angle distance measure. The recognition rate and computational cost of proposed approach is examined against different wavelet families and Euclidean distance measure. Feature extraction is performed using Discrete wavelet transform and Principal component analysis (DWT-PCA). In order to explore best features, experiments are carried out for DWT subband selection and for DWT wavelet selection on Symlet family and on four other different wavelet families (Daubechies, Coiflets, Discrete Meyer and Biorthogonal wavelet family). This also includes their members that vary in terms of orthogonality, symmetry, support size, vanishing moments and filter order. After generating feature vectors, classification is done by Cosine angle distance measure based nearest neighbor classifier (NNC) and its results are compared with Euclidean distance measure. As test dataset, AT&T database of 400 images of 40 people is used to establish the performance by proposed approach. Experimental results on Symlet-6 with Cosine angle distance measure based nearest neighbor classifier shows highest percentage recognition rate of 98.33 for randomly generated 120 image training set.","PeriodicalId":294210,"journal":{"name":"2016 Ninth International Conference on Contemporary Computing (IC3)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129320014","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: 10

Automatic imaging method for optic disc segmentation using morphological techniques and active contour fitting 基于形态学和主动轮廓拟合的视盘分割自动成像方法

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880227

Ashi Agarwal, Ashish Issac, Anushikha Singh, M. Dutta

引用次数: 11

Range clustering: An algorithm for empirical evaluation of classical clustering algorithms 范围聚类:一种对经典聚类算法进行经验评价的算法

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880242

N. Arora, Sandeep Jain, S. Verma

{"title":"Range clustering: An algorithm for empirical evaluation of classical clustering algorithms","authors":"N. Arora, Sandeep Jain, S. Verma","doi":"10.1109/IC3.2016.7880242","DOIUrl":"https://doi.org/10.1109/IC3.2016.7880242","url":null,"abstract":"Cluster analysis is a principal method in analytics domain of data mining. The algorithm used for clustering directly influences the results obtained from applying the clustering algorithm (clusters). Data clustering is done in order to identify the patterns and trends not identifiable from just looking at the data. Clustering may be supervised (if the machine training data set is available) or unsupervised (if the machine training data set is not available). Unsupervised clustering is usually done using k-Means Algorithm (using any distance, the most common being Euclidean and Manhattan Distance). The drawback of k-means algorithm for a large set are the rigorous calculations that need to be done to cluster a data set into multiple data subsets for every single iteration, thereby limiting its efficiency and use for large data sets. We propose a range based single pass clustering algorithm that clusters data on the basis of the range which it falls in, where the ranges are calculated using simple arithmetic mean between two values. The proposed algorithm is compared against the standard k-means algorithm (using Euclidean Distance and Manhattan Distance).","PeriodicalId":294210,"journal":{"name":"2016 Ninth International Conference on Contemporary Computing (IC3)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122278825","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: 3

Sentiment mining: An approach for Bengali and Tamil tweets 情感挖掘:孟加拉语和泰米尔语推文的一种方法

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880246

SudhaShanker Prasad, J. Kumar, D. Prabhakar, S. Tripathi

引用次数: 13

Hybridization of gravitational search algorithm and biogeography based optimization and its application on grid scheduling problem 重力搜索算法与生物地理优化的融合及其在电网调度问题中的应用

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880211

Lavika Goel, Sunita Singhal, S. Mishra, Satyajit Mohanty

{"title":"Hybridization of gravitational search algorithm and biogeography based optimization and its application on grid scheduling problem","authors":"Lavika Goel, Sunita Singhal, S. Mishra, Satyajit Mohanty","doi":"10.1109/IC3.2016.7880211","DOIUrl":"https://doi.org/10.1109/IC3.2016.7880211","url":null,"abstract":"The Gravitational Search Algorithm (GSA) is a nature inspired optimization algorithm which is based on Newton's law of gravity and law of motion. Biogeography Based Optimization (BBO) is also another nature inspired optimization algorithm based on the concept of biogeography (migration and mutation among population). Both of these optimization technique are population based and individually have been applied to a large number of areas. In this paper, we are providing a hybrid GSABBO algorithm that will use the best properties of both the algorithm to enhance the exploration and exploitation properties and reach at the global optimal solution. Grid Computing refers to the sharing of resources across multiple domains to achieve a common goal. Sharing of the resources within an organization helps to enhance its overall performance computationally and economically. The advantages derived from Grid Computing are largely dependent on the scheduling algorithm we use to schedule various jobs across various resources available. This paper introduces a new approach based on the hybridization of BBO and GSA to generate optimal schedules to complete all the given tasks with minimum make span period.","PeriodicalId":294210,"journal":{"name":"2016 Ninth International Conference on Contemporary Computing (IC3)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130124138","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: 5

An automated imaging algorithm for macula detection in fundus images 眼底图像中黄斑检测的自动成像算法

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880226

Anushikha Singh, Namita Sengar, Ashish Issac, M. Dutta

引用次数: 1

Frame structures for hybrid spectrum accessing strategy in cognitive radio communication system 认知无线电通信系统中混合频谱接入策略的框架结构

2016 Ninth International Conference on Contemporary Computing (IC3) Pub Date : 2016-08-01 DOI: 10.1109/IC3.2016.7880206

P. Thakur, Alok Kumar, S. Pandit, G. Singh, S. N. Satashia

引用次数: 10