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Nānded, India

Vaidya S.,SGGSIET
International Conference and Workshop on Emerging Trends in Technology 2011, ICWET 2011 - Conference Proceedings | Year: 2011

This project aims at low bit rate videos. There are various techniques available like MPEG 4, WMV, and H.264/AVC which does the same. In this project H.264/AVC has been modified to further reduce the bit rate of the videos. Quality lowers down a bit but the bit rate which is of utmost important criteria for the limited bandwidth factor is achieved. Copyright © 2011 ACM. Source


Patil D.O.,SGGSIET
11th IEEE India Conference: Emerging Trends and Innovation in Technology, INDICON 2014 | Year: 2015

In this paper new technique called 'KITE' is implemented for brain tumor growth analysis. This is done by using gray images pixel count inside kite shape boundaries. We also differentiated gray color shades to focus over the outgrowth of tumor. As we know in medical field, countless radiological and pathological images in advanced organization are developed commonly in clinics and medical focuses with refined picture securing gadgets and computerized scanners. Medical images are for the most part intricate in nature and are utilized for diagnosis, therapy, exploration and training. Our implemented KITE technique proves the most cost effective and high precision application for detection of brain tumor. © 2014 IEEE. Source


Vipparthi S.K.,Malaviya National Institute of Technology, Jaipur | Murala S.,Indian Institute of Technology Ropar | Gonde A.B.,SGGSIET | Wu Q.M.J.,University of Windsor
IET Computer Vision | Year: 2016

This study proposes a new feature descriptor, local directional mask maximum edge pattern, for image retrieval and face recognition applications. Local binary pattern (LBP) and LBP variants collect the relationship between the centre pixel and its surrounding neighbours in an image. Thus, LBP based features are very sensitive to the noise variations in an image. Whereas the proposed method collects the maximum edge patterns (MEP) and maximum edge position patterns (MEPP) from the magnitude directional edges of face/image. These directional edges are computed with the aid of directional masks. Once the directional edges (DE) are computed, the MEP and MEPP are coded based on the magnitude of DE and position of maximum DE. Further, the robustness of the proposed method is increased by integrating it with the multiresolution Gaussian filters. The performance of the proposed method is tested by conducting four experiments onopen access series of imaging studies-magnetic resonance imaging, Brodatz, MIT VisTex and Extended Yale B databases for biomedical image retrieval, texture retrieval and face recognition applications. The results after being investigated the proposed method shows a significant improvement as compared with LBP and LBP variant features in terms of their evaluation measures on respective databases. © The Institution of Engineering and Technology 2016. Source


Shaikh N.F.,College of Engineering, Pune | Doye D.D.,SGGSIET
Journal of Intelligent and Fuzzy Systems | Year: 2016

Iris Recognition that emerged two decades back has a number of algorithms developed and vast amount of work has been carried out since its inception. Iris recognition uses pattern-recognition techniques based on high-resolution images of the person. This paper proposes a novel iris recognition system using FFBNN-ACFO. Initially the given input images are preprocessed using adaptive median filter to remove noise. Then the features which are extracted from the preprocessed image are used to train the FFBNN. During training, FFBNN parameters are optimized by ACFO to get high recognition accuracy. In the testing phase sufficient number of iris images, are utilized to analyze the performance of the proposed iris recognition system. The results of the proposed method are compared with FFBNN-AAPSO, FFBNN-PSO, and FFBNN techniques. The comparison result shows that the proposed iris recognition system based on FFBNN-ACFO, gives higher recognition accuracy than the existing iris recognition systems. © 2016 -IOS Press and the authors. All rights reserved. Source


Kamble D.N.,AVCOE | Nandedkar V.M.,SGGSIET
Applied Artificial Intelligence | Year: 2010

The connecting rod is among the most important part used in various engines. With increasing demand for geometrical dimensional accuracy and internal quality, the forging of connecting rod is under investigation. The study deals with an analytical approach in regard to design of knowledge base of an expert system for forging connecting rods. The proposed analytical relations are based on the SLAB method modified by introducing the temperature-dependent flow stress and empirical set of relations for flash dimensions. The overall approach is designed to predict the flash load and cavity load contribution to total load. The cavity stress, flow stress, and principal stresses are also predicted at three different sections of the connecting rod with respect to temperature. The obtained results are verified by a literature comparison and are validated by conducting experiments. The expert system is designed based on the application of VISUAL BASIC language. Copyright © 2010 Taylor & Francis Group, LLC. Source

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