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72 results on '"Kaluri, Rajesh"'

51. Optimized Feature Extraction for Precise Sign Gesture Recognition Using Self-improved Genetic Algorithm

Author

Kaluri, Rajesh, CH, Pradeep Reddy, Kaluri, Rajesh, and CH, Pradeep Reddy

Abstract

Over the past two years, gesture recognition has become the powerful communication source to the hearing-impaired society. Furthermore, it is supportive in creating interaction between the human and the computer. However, the intricacy against the gesture recognition arises when the environment is relatively complex. In this paper, recognition algorithm with feature selection based on Self-Improved Genetic Algorithm (SIGA) is proposed to promote proficient gesture recognition. Furthermore, the recognition process of this paper includes segmentation, feature extraction and feed- forward neural network classification. Subsequent to the gesture recognition experiment, the performance analysis of the proposed SIGA is compared with the conventional methods as reported in the literature along with standard Genetic Algorithm (GA). In addition, the effect of optimization and the feature sensitivity is also demonstrated. Thus, this method makes aggregate performance against the conventional algorithms.

Published
2018

56. An Enhanced Framework for Sign Gesture Recognition using Hidden Markov Model and Adaptive Histogram Technique.

Author

Kaluri, Rajesh and C. H., Pradeep Reddy

Subjects
PATTERN recognition systems, ADAPTIVE computing systems, HIDDEN Markov models, FEATURE extraction, WIENER filters (Signal processing)
Abstract

Gesture based communication is the fundamental method for correspondence for those with hearing and vocal incapacities. Communication via gestures comprises of making shapes or developments with human hands as for the head or other body parts. In this paper, we propose a new framework for recognizing sign gestures by using Hidden Markov Model (HMM) and Histogram based methods. Initially, the noise of an image will be eliminated by Wiener Filter and the image will be segmented with the help of Histogram oriented methods - Adaptive Histogram technique and then features will be extracted. The extracted features will be given to the HMM for training and recognition of gestures. Our experimental results show a better performance in terms of recognizing gestures from a blurred image compared to the existing segmentation methods. [ABSTRACT FROM AUTHOR]

Published
2017
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69. Inclusive Virtual Reality Learning Environment

Author

Rūdolfa, Astra, Daniela, Linda, Zālīte-Supe, Zinta, Mahmud, Mufti, Series Editor, Kaiser, M. Shamim, Series Editor, Kaluri, Rajesh, editor, Gadekallu, Thippa Reddy, editor, Rajput, Dharmendra Singh, editor, and Lakshmanna, Kuruva, editor

Published
2024
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72. BIG data based on healthcare analysis using IOT devices

Author

Kaluri, Rajesh, Lakshmanna, Kuruva, and Kumar, Praveen

Abstract

IOT (INTERNET OF THINGS) makes the brilliant protest in social insurance. The heterogeneous registering, remotely imparting arrangement of gadget that interfaces with human body and wellbeing gave to analyse, screen, track and store virtual factual and restorative data. In this paper, quiet individual data and wellbeing condition will be dissect by the specialist and they can see the patient condition and furthermore give the correct answer for the patient. The more number of information (huge information) will store and move into the specific association record framework. It makes conceivable to social occasion of rich data demonstrative of our physical and psychological wellness.

Published
2017

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