K. Venkatalakshmi

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This paper focusses on classification of multispectral images based on hybrid clustering using SVM and ML classifiers. Hybrid clustering combines both PSO and K-means clustering. K-means clustering is done initially and the result is used to seed the initial swarm. Based on these clusters, classification is done using ML and SWM classifiers. The results of(More)
In the recent years, the rapid advancement of computer networks has led to many security problems by malicious users to the modern computer systems. Hence, it is necessary to detect illegitimate users by monitoring the unusual user activities in the network. In this paper, we propose an Intrusion Detection System (IDS) which uses a genetic algorithm based(More)
In this paper, intelligent algorithms for intrusion detection are proposed which detect the network attacks as normal or anomaly based attacks by performing effective preprocessing and classification. This system uses a new genetic algorithm approach for pre-processing and Modified J48 classification algorithm to identify the intended activities. The new(More)
E-Learning is a fast, just-in-time, and non-linear learning process, which is now widely applied in distributed and dynamic environments such as the World Wide Web. Ontology plays an important role in capturing and disseminating the real world knowledge for effective human computer interactions. However, engineering of domain ontologies is very labor(More)
Efficient consumption of energy of sensor node in Wireless Sensor Networks (WSN's) is one of the noticeable challenges nowadays. We can prolong the lifetime of WSN by well-organized clustering of nodes. In this work we suggest PSO incorporated cuckoo search optimization algorithm for clustering in energy aware way and compared it with cuckoo search(More)
An attempt has been made in the paper to find globally optimal cluster centers for remote-sensed images with the proposed Rapid Genetic k-Means algorithm. The idea is to avoid the expensive crossover or fitness to produce valid clusters in pure GA and to improve the convergence time. The drawback of using pure GA in the problem is the usage of an expensive(More)
In this work a PSO based algorithm has been proposed to improve the sturdiness against RS steganalysis. RS Steganalysis is commonly used method which detects the steg-message from the stego-image. A new method based on particle swarm optimization is proposed in this paper to improve the robustness of the stego image against RS steganalysis. The pixel values(More)
Artificial neural networks have gained increasing popularity as an alternative to statistical methods for classification of remote sensed images. The superiority of neural networks is that if they are trained with representative training samples they show improvement over statistical methods in terms of overall accuracies. However if the distribution(More)
Particle Swarm Optimization (PSO) modified to solve image processing problem with reference to enhancement technique is proposed in this paper. The enhancement process is an optimization problem with several constraints. The objective of the proposed PSO is to maximize an objective fitness criterion in order to improve the contrast and detail in an image by(More)
One of the harmful diseases among females in the world is breast cancer. Breast cancer leftovers a noteworthy scientific, clinical and communal challenge. Ultrasound is high-frequency sound wave used to capture images of internal organs of a human. Failure of detection in mammogram can be seen in an ultrasound. This work proposes an efficient scheme to(More)