Supervised chromosome clustering and image classification
TL;DR: In this paper, the distance and similarities play an important role, where the greater the dissimilarity measure or distance of genes, the more dissimilar are the two chromosomes.
About: This article is published in Future Generation Computer Systems.The article was published on 2011-04-01. It has received 3 citations till now. The article focuses on the topics: Cluster analysis & Contextual image classification.
Citations
More filters
01 Jul 2014
TL;DR: The proposed GOA first combines multiple well-known FS techniques to yield a possible optimal feature subsets across different traffic datasets; then the proposed adaptive threshold, which is based on entropy to extract the stable features.
Abstract: There is significant interest in the network management community about the need to identify the most optimal and stable features for network traffic data. In practice, feature selection techniques are used as a pre-processing step to eliminate meaningless features, and also as a tool to reveal the set of optimal features. Unfortunately, such techniques are often sensitive to a small variation in the traffic data. Thus, obtaining a stable feature set is crucial in enhancing the confidence of network operators. This paper proposes an robust approach, called the Global Optimization Approach (GOA), to identify both optimal and stable features, relying on multi-criterion fusion-based feature selection technique and an information-theoretic method. The proposed GOA first combines multiple well-known FS techniques to yield a possible optimal feature subsets across different traffic datasets; then the proposed adaptive threshold, which is based on entropy to extract the stable features. A new goodness measure is proposed within a Random Forest framework to estimate the final optimum feature subset. Experimental studies on network traffic data in spatial and temporal domains show that the proposed GOA approach outperforms the commonly used feature selection techniques for traffic classification task.
49 citations
01 Jan 2015
TL;DR: In recent years, knowing what information is passing through the networks is rapidly becoming more and more complex due to the ever-growing list of applications shaping today's Internet traffic.
Abstract: In recent years, knowing what information is passing through the networks is rapidly becoming more and more complex due to the ever-growing list of applications shaping today's Internet traffic. Consequently, traffic monitoring and analysis have become cr
6 citations
28 Feb 2016
TL;DR: The experimental results demonstrate that the non-fuzzy algorithms have higher accuracies in compared to the fuzzy algorithms, especially when dealing with large data sizes and different types of images.
Abstract: This paper classifies different digital images using two types of clustering algorithms. The first type is the fuzzy clustering methods, while the second type considers the non-fuzzy methods. For the performance comparisons, we apply four clustering algorithms with two from the fuzzy type and the other two from the non-fuzzy (partitonal) clustering type. The automatic partitional clustering algorithm and the partitional k-means algorithm are chosen as the two examples of the non-fuzzy clustering techniques, while the automatic fuzzy algorithm and the fuzzy C-means clustering algorithm are taken as the examples of the fuzzy clustering techniques. The evaluation among the four algorithms are done by implementing these algorithms to three different types of image databases, based on the comparison criteria of: dataset size, cluster number, execution time and classification accuracy and k-cross validation. The experimental results demonstrate that the non-fuzzy algorithms have higher accuracies in compared to the fuzzy algorithms, especially when dealing with large data sizes and different types of images. Three types of image databases of human face images, handwritten digits and natural scenes are used for the performance evaluation.
References
More filters
Proceedings Article•
01 Jan 2007
9 citations
"Supervised chromosome clustering an..." refers methods in this paper
...Pass the images through the thinning algorithm [18]....
[...]
26 Aug 2007
TL;DR: This proposed scheme could be applied for ownership protection, copy control, annotation and authentication of digital media, and is focused on authentication of handwritten signature.
Abstract: In this paper, we propose data hiding, extraction and handwritten signature authentication algorithms for binary images. Handwritten signature Image can be transmitted from source to target securely over network after processing the source image by using this proposed data hiding algorithm. According to the algorithm, size of the carrier image must be double (or more) the size of source image. If necessary then additional bytes or noise needed to be injected into carrier image to attain the required size. To do this, the header is updated by the new value (sum of original size of file and amount of noise). There are numerous biometric authentication methods also proposed. In this paper, we propose a novel and new alternative. Entire work can be divided into two phases- a. security on transmission; and b. Recognition and authentication. Our scheme supports the application environment and we strongly believe that "user authentication by statistical analysis" could be a solid platform for future research and study. This proposed scheme could be applied for ownership protection, copy control, annotation and authentication of digital media. This work is focused on authentication of handwritten signature.
8 citations
26 Aug 2007
TL;DR: The two dimensional store separation with trajectory mode of three-DOF is computed in an unsteady flow field and Euler equations are solved for two/three-dimensional steady state flow fields.
Abstract: A technique for the generation of overlapped grid using a simple shooting method, that is a cut-paste algorithm, is presented. It makes possible to generate overlapping grids with moderate mesh interface region. To generate overlapped grids with minimal amount of user inputs, the advancing-front technique using the fringe points as facets is used. To remove hole points initially, fronts using solid bodies and the zones of interference algorithm are used. The overlapped grids are generated for several cases using present algorithms and Euler equations are solved for two/three-dimensional steady state flow fields. To demonstrate the capability of present method, the two dimensional store separation with trajectory mode of three-DOF is computed in an unsteady flow field.
6 citations
24 Apr 2008
TL;DR: A new handwritten signature authentication scheme based on extensive statistical analysis, Mean variance and theory of estimation that supports the application environment and could be a solid platform for future research and study.
Abstract: In this paper we propose a new handwritten signature authentication scheme. The scheme consists of two main rule set algorithms and one authentication algorithm. The Algorithms are based on extensive statistical analysis, Mean variance and theory of estimation. This is an extension work of handwritten signature identification. This scheme supports the application environment and we strongly believe that "user authentication" could be a solid platform for future research and study.
3 citations
"Supervised chromosome clustering an..." refers background in this paper
...This is very common, because, algorithm(s) have to handle large sets of image data [19]....
[...]