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Methods for Text Segmentation from Scene Images
(2017-09-27)
Recognition of text from camera-captured scene/born-digital images help in the development of aids for the blind, unmanned navigation systems and spam filters. However, text in such images is not confined to any page layout, ...
Discovering Frequent Episodes With General Partial Orders
(2013-06-04)
Pattern Discovery, a popular paradigm in data mining refers to a class of techniques that try and extract some unknown or interesting patterns from data. The work carried out in this thesis concerns frequent episode mining, ...
The Multiprocessor Scheduling Of Periodic And Sporadic Hard Realtime Systems
(2013-10-04)
Real time systems have been a major area of study for many years. Advancements in electronics, computers, information technology and digital networks are fueling major changes in the area of real time systems. In this ...
Lexicon-Free Recognition Strategies For Online Handwritten Tamil Words
(2014-08-07)
In this thesis, we address some of the challenges involved in developing a robust writer-independent, lexicon-free system to recognize online Tamil words. Tamil, being a Dravidian language, is morphologically rich and also ...
Neural Architectures For Active Contour Modelling And For Pulse-Encoded Shape Recognition
(2014-09-12)
An innate desire of many vision researchers IS to unravel the mystery of human
visual perception Such an endeavor, even ~f it were not wholly successful, is expected to yield byproducts of considerable significance to ...
Multiview Face Detection And Free Form Face Recognition For Surveillance
(2014-10-15)
The problem of face detection and recognition within a given database has become one of the important problems in computer vision. A simple approach for Face Detection in video is to run a learning based face detector every ...
Supervised Learning of Piecewise Linear Models
(2018-03-07)
Supervised learning of piecewise linear models is a well studied problem in machine learning community. The key idea in piecewise linear modeling is to properly partition the input space and learn a linear model for every ...

