Avik Bhattacharya

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In this paper the aim of the study is to improve the dynamic performance of a shunt-type active power filter. The predictive and adaptive properties of artificial neural networks (ANNs) are used for fast estimation of the compensating current. The dynamics of the dc-link voltage is utilized in a predictive controller to generate the first estimate followed(More)
PAPERS Multiphase Systems Parallel-Connected Shunt Hybrid Active Power Filters Operating at Different Switching Frequencies for Improved Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Bhattacharya, C. Chakraborty, and S. Bhattacharya 4007 Simulation of the Electromagnetic Response Characteristic of an Inductively Filtered(More)
This letter addresses the problem of unsupervised land-cover classification of remotely sensed multi-spectral satellite images from the perspective of cluster ensembles and selflearning. The cluster ensembles combine multiple data partitions generated by different clustering algorithms into a single robust solution. A cluster ensemble based method is(More)
This paper addresses the problem of land-cover classification of remotely sensed image pairs in the context of domain adaptation. The primary assumption of the proposed method is that the training data are available only for one of the images (source domain) whereas for other image (target domain), no labeled data are available. No assumption is made here(More)
Retrieval from remote sensing image archives relies on the extraction of pertinent information from the data about the entity of interest (e.g. land cover type), and on the robustness of this extraction to nuisance variables (e.g. illumination). Most image-based characterizations are not invariant to such variables. However, other semantic entities in the(More)
We address the problem of automatic land-cover map updating of multi-temporal and multi-spectral remotely sensed images in this paper. Given a pair of images acquired on the same geographical area at two distinct time instants, it is assumed here that the training data are available for one of the acquisitions, which is known as the source domain image. The(More)
Indexing and retrieval from remote sensing image databases relies on the extraction of appropriate information from the data about the entity of interest (e.g. land cover type) and on the robustness of this extraction to nuisance variables. Other entities in an image may be strongly correlated with the entity of interest and their properties can therefore(More)