A Study of Credit Guarantee Fund Trust for Micro and Small Enterprises with particular reference to Bank of Baroda in state of Kerala

While the quantum of advances from the public sector banks (PSBs) to the MSEs has increased over the years in absolute terms, from Rs.46, 045 crore in March 2000 to Rs.1, 85,208 crore in March 2009, the share of the 7credit to the MSE sector in the Net Bank Credit (NBC) has declined from 12.5 per cent to 10.9 per cent. Similarly, there has been a decline in the share of micro sector as a percentage of Net Bank Credit (NBC) from 7.8 per cent in March 2000 to 4.9% in March 2009. (TKA.Nair, 2010)9.The major reasons for low availability of bank finance to this sector are high risk perception of the banks in lending to MSEs and high transaction costs in processing of loan applications of MSEs. The problem is more serious for micro enterprises requiring small loans and the first generation entrepreneursThe thesis studies the divergence in guidelines by, CGTMSE, RBI & Bank of Baroda on collateral free lending and analyses the awareness of MSE about CGTMSE lending. The researcher tries to assess the problems faced by borrowers in availing advance under CGTMSE from Bank of Baroda, Kerala.

Single Frame Image Super Resolution Using Learned Directionlets

In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. This method uses directionlets to effectively capture directional features and to extract edge information along different directions of a set of available high resolution images .This information is used as the training set for super resolving a low resolution input image and the Directionlet coefficients at finer scales of its high-resolution image are learned locally from this training set and the inverse Directionlet transform recovers the super-resolved high resolution image. The simulation results showed that the proposed approach outperforms standard interpolation techniques like Cubic spline interpolation as well as standard Wavelet-based learning, both visually and in terms of the mean squared error (mse) values. This method gives good result with aliased images also.