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Load disaggregation involves identification of the operating appliances and their respective power consumption using only total building power consumption data. Load disaggregation also called as non-intrusive load monitoring can offer consumers greater visibility about their individual appliance power consumption. This information will help customers (i) to optimize the use of appliances, resulting...
In this paper, a hybrid approach is presented for tracking control of redundant robot manipulators. In this approach, an RBF(Radial Basis Function) neural controller and an adaptive bound is added to the model based controller i.e (CT type controller). The hybrid controller achieves end-effector tracking as well as subtask tracking adequately. The RBF network learns all the existing uncertainties...
We formulate the problem of single image super resolution (SR) in terms of learning a single but general nonlinear function. This function takes a low resolution (LR) image patch input and predicts the high resolution (HR) image pixels corresponding to the center pixel of the patch. For training, we use a LR version of an input image, and the given image pixels as target, thus obviating the need for...
We develop a wavelet domain learning based technique for single image super resolution (SISR). First, we learn a mapping between a patch of approximate coefficients (ACs) and the detail coefficients (DCs) corresponding the center location of the patch using Neural Networks. We then obtain an SR image by using an approximate version of the original image (scaled as per the DWT size requirements of...
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