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RISS 인기검색어
- 검색키워드
- 저자 : Shashidhar Ram Joshi (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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A Chunk Level Statistical Machine Translation
Shashidhar Ram Joshi,Arjun Singh Saud,Jagadish Bhatta,Ashim Ghishing,Bikash Balami,Yoga Raj Joshi 한국멀티미디어학회 2010 한국멀티미디어학회 국제학술대회 Vol.2010 No.-
Machine Translation (MT) is a task of translating from one language to another by the use of computer. The peculiarities and morphological structures' differences among languages create ambiguity and make MT more challenging. This paper is mainly concentrated on Chunk Level Statistical Machine Translation (SMT) rather than the traditional rule-based translation. SMT acquires knowledge that is required for the statistical translation by training. This training is conducted over the bilingual corpus. The knowledge, which is typically in the form of probabilities of various language features, is used to guide the translation process. The paper overviews an SMT technique which is implemented for English to Nepali translation and discusses some issues related with the translation ambiguities such as gender ambiguities, dropping words, unknown words etc.
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Tracking Eye Movement for Visual Cursor
Shashidhar Ram Joshi,Laxmi Rayamajhi Rawal 한국멀티미디어학회 2010 한국멀티미디어학회 국제학술대회 Vol.2010 No.-
To design a real-time, robust eye tracker system with human eye movement indication property using the movements of eye pupil an algorithm is designed. Eye tracker algorithm is implemented using the Continuously Adaptive Mean-Shift (CAMSHIFT) algorithm and the EigenFace method. Input image captured by the web cam is detected using the CAMSHIFT algorithm. Face area is passed through a number of steps such as color space conversion and thresholding. After these steps, areas for left and right eyes are determined using the geometrical properties of the human face. Search regions for left and right eyes are individually passed to the eye detection algorithm to determine the exact locations of each eye.
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New Algorithm in the Particle Tracking Velocimetry using Self-Organizing Map
Joshi Shashidhar Ram 한국멀티미디어학회 2010 한국멀티미디어학회 국제학술대회 Vol.2010 No.-
The self-organizing maps (SOM) model seems to have turned out particularly effective for the particle tracking algorithm of the PIV system. This is mainly because of the performance of the particle tracking itself, capacity of dealing with unpaired particles between two frames and no necessity for a priori knowledge on the flow field (e.g. maximum flow rate) to be measured. Initially, concept of SOM was applied to PIV by Labonte. It was modified by Ohmi and further modified algorithm is developed using the concept of Delta-Dar-Delta rule. It is a heuristic algorithm for modifying the learning rate as training progresses. Earlier, the treatment of unpaired particles, a specific problem to any type of PIV, is not fully considered and thereby, the tracking goes unsuccessfully for some particles. The present research is to bring about further improvement and practicability in this promising particle tracking algorithm. The computational complexity can be reduced employing modified algorithm compared to other algorithms. The modified algorithm is tested in the light of the synthetic PIV standard image as well as in particle images obtained from visualization experiments.
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