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Eswar Reddy, B.
- An Overview of Pattern Recognition Methods on Texture Classification
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In this paper three basic approaches of pattern recognition are analyzed: statistical pattern recognition, structural pattern recognition and neural pattern recognition. In the statistical approach the recognition is based on the decision boundaries that are established in the feature space by statistical distribution of the patterns. In the structural (syntactic) approach each pattern class is defined by a structural description or representation. The recognition is performed according to the similarity of structures. This is based on the fact that the significant information is not only the features but also the relationships consisting among the features. In the neural network based approach the artificial neural networks are able to form complex decision regions for pattern recognition. The present work involves in the study of Pattern recognition methods on Texture Classifications.
Authors
Affiliations
1 Department of IT, AITS, Rajampet, Andhra Pradesh, IN
2 Dept. of CSE, JNT University, Anantapur, Andhra Pradesh, IN
1 Department of IT, AITS, Rajampet, Andhra Pradesh, IN
2 Dept. of CSE, JNT University, Anantapur, Andhra Pradesh, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 7 (2011), Pagination: 426-430Abstract
Pattern recognition (PR) is a subject that deals with the identification or interpretation of the pattern in an image. It aims to extract information about the image to classify its contents. Inputs are in the form of digitized binary valued 2D images or textures containing the pattern to be classified. The analysis and recognition of the patterns such as images and textures are becoming more and more complex and multiform. This is because in general the patterns to be analyzed are shifting from simple to complex, and because the patterns of heavy variations and with heavy noise have to be treated. Therefore it is proposed to develop sophisticated strategies of pattern analysis to cope with these difficulties.In this paper three basic approaches of pattern recognition are analyzed: statistical pattern recognition, structural pattern recognition and neural pattern recognition. In the statistical approach the recognition is based on the decision boundaries that are established in the feature space by statistical distribution of the patterns. In the structural (syntactic) approach each pattern class is defined by a structural description or representation. The recognition is performed according to the similarity of structures. This is based on the fact that the significant information is not only the features but also the relationships consisting among the features. In the neural network based approach the artificial neural networks are able to form complex decision regions for pattern recognition. The present work involves in the study of Pattern recognition methods on Texture Classifications.
Keywords
Pattern Recognition, Texture, Neural Networks, Classification.- India’s Participation in the Thirty Meter Telescope International Observatory Project
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Authors
Affiliations
1 Indian Institute of Astrophysics, 2nd Block, Koramangala, Bengaluru 560 034, IN
2 Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411 007, IN
1 Indian Institute of Astrophysics, 2nd Block, Koramangala, Bengaluru 560 034, IN
2 Inter-University Centre for Astronomy and Astrophysics, Post Bag 4, Ganeshkhind, Pune 411 007, IN
Source
Current Science, Vol 113, No 04 (2017), Pagination: 631-638Abstract
The Thirty Meter Telescope International Observatory (TIO) is being built by an international consortium of institutes and universities in Canada, China, India, Japan and USA. The estimated cost is about US$ 1.47 billion (2012 base year). At present, it is planned to be built on Mauna Kea, Hawaii, at an altitude of about 4000 m. The mountain is already home to many of the world's largest telescopes. The Union Cabinet chaired by the Prime Minister, at its meeting held on 24 September 2014, approved India's participation in the TIO project at a total cost of Rs 1299.80 crores. Only about 30% of India's contribution to the project will be made in cash to be utilized for building common facilities and infrastructure. The rest will be made through design, development and manufacturing of a number of hardware, software and optical components. India's participation in the TIO is an extramural national project jointly funded by the Department of Science and Technology (DST) and the Department of Atomic Energy (DAE). To successfully deliver India's in-kind contributions, the two funding agencies have jointly set up the India TMT Coordination Centre (ITCC) which is located at the Indian Institute of Astrophysics (IIA), Bengaluru. IIA along with the Aryabhatta Research Institute of Observational Sciences, Nainital and the Inter-University Centre for Astronomy and Astrophysics, Pune are the key institutes which manage the India TMT project through ITCC. Being a major extra-mural national effort, several other institutes as well as universities participate in the technological, developmental and scientific aspects of the initiative.Keywords
Actuators, Coating Chambers, Edge Sensors, International Observatory Project, Segment Support Assembly.References
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