Marimuthu Krishnaveni

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Research in Automatic Speech Recognition (ASR) has attracted a great deal of attention over the past five decades. It aims to provide an efficient way for human to communicate with computers. With the extensive development of these systems permits the user to talk almost naturally with computers. Hence, today's researchers are mainly focusing on developing(More)
Synthetic Aperture Radar (SAR) techniques represent a promising alternative compared to traditional surveillance methods. The capabilities of satellite based SAR systems are confirmed and specific data exploitation methods are still to be developed to provide an efficient automatic interpretation of SAR data. The mean of this paper is to analyze and compare(More)
Segmentation of target is an important step in forming realistic target models. To assist in classifying the relevant literature, two types of segmentation are identified where each type adds its own additional level of uniqueness. The first type is composed of the simplest forms of image analysis through thresholding, the second is characterized by region(More)
The textile industries by for the most passionate user of synthetic dyes are in need of ecoefficient solutions for its coloured effluents. The decolorization and detoxification potential of white rot fungi can be harnessed. Laccase has been utilized in biological treatment of effluents containing chemical dyes. The present study is planned to study the(More)
The ionosphere is defined as a region of the earth's upper atmosphere where sufficient ionisation can exist to affect the propagation of radio waves. Estimation of missing data of ionosphere total electron content (TEC) are crucial and remain a challenge for GPS positioning and navigation system, space weather forecast, as well as many other Earth(More)
The need of sign language is increasing radically especially to hearing impaired community. Only few research groups try to automatically recognize sign language from video, colored gloves and etc. Their approach requires a valid segmentation of the data that is used for training and of the data that is used to be recognized. Recognition of a sign language(More)
In the emerging trend of speech technologies, speech/non-speech detection is an unsolved problem, which affects numerous speech related applications. Especially in robust speech recognition, there is always a need for a noise reduction scheme working in combination with a precise Voice Activity Detector (VAD). The approach in this paper is based on(More)
Digital images are prone to a variety of types of noise. Noise is the result of errors in the image acquisition process that result in pixel values that do not reflect the true intensities of the real scene (Gagnon & Smaili, 1996). There are several ways that noise can be introduced into an image, depending on how the image is created. For example if the(More)
Most the objective of intelligent systems is to create a model, which given a minimum amount of input data or information, is able to produce reliable recognition rates and correct decisions. In the application, when an individual classifier has reached its limit and, at the same time, it is hard to develop a better one, the solution might only be to(More)
With the growing capacity of computer vision technology, there is more interest being directed towards the automatic recognition of sign language based solely on image sequences or videos. In this paper a well-built segmentation process is developed which helps to promote a better vision-based sign language recognition system. Segmentation is a challenging(More)