International Journal of Technology

P. K. Singh ¹, Narendra Pal Singh ¹

Affiliations
1 Department of Computer Science and Engineering, Madan Mohan Malaviya Engineering College, Gorakhpur-273010, IN

Abstract

Security is an essential part of wired and wireless network communication. Interestingly enough, these systems are designed to provide to open access across vast networked environments. Today's technologies are usually networkoperation- intrusive, i.e. they often limit connectivity and inhibit easier access to data and services. With the increasing popularity of wireless network, the security issue for end users could be even more serious then we expect. In wireless communication technology, a new networking technique, Ad-hoc wireless sensor network is currently under research. It has drawn much attention from researchers and user in recent years because it provides several application scopes for users and major challenges for researchers. Technical publications and conferences basically focusing on WSN technology and applications are commonplace. Research, development, and manufacturing of these networks are thriving. Many applications for WSNs have been proposed, but few are operational and many technical issues about WSNs remain to be solved by researchers. In this paper we present a summary on the security mechanisms issues and problems of current WSN technology. Of primary importance, the security issues facing WSNs are many and varied.

Keywords

Ad-Hoc Network, Wireless Network, Sensor Node, Routing, Security, Attack.

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Pramod Kumar Pandey ¹, P. K. Singh ¹

Affiliations
1 MM Engineering College, Gorakhpur, IN

Abstract

Image parsing is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. For instance, for a database of horse images, image parsing can be thought of as the task of classifying each pixel as part of a horse or nonhorse. In more complicated problems, image parsing might require multiple labels, e.g. roads, cars, houses etc. in outdoors scenes. Clearly, pixels can not be classified in this manner based only on their intensities or even local feature descriptors. Contextual information plays a critical role in resolving ambiguities. Image parsing can be posed as a supervised learning problem where a classifier is learnt from training data consisting of images and corresponding label maps. Autocontext and convolutional networks are two promising approaches that apply context to image parsing in the supervised learning setting.

Keywords

Parsing, Autocontext, Supervised.

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