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In this paper, a fuzzy approach on the neighbourhood metric is proposed for usage with Histogram equalization for image contrast enhancement. The Neighbourhood Metrics or local image properties are used to sub divide the large histogram bins produced by Global Histogram Equalization. Large histogram bins in the image causes visual deteriorations. We propose, a fuzzy approach to sub divide the large...
Fusion is a process of extraction of useful information acquired from several domains. The objective of image fusion is to extract the needed data from multiple images to generate a composite image that contains an enhanced representation of the image than any individual source image. Image fusion can be applied to various images like multi-sensor, multi-modal, multi-temporal or multi-focus. The reason...
The German SpaceBot Cup is a robotics competition that has its first edition in 2013. A second edition is expected by the end of 2015. The SpaceBot application scenario involves typical exploration tasks carried out on a planetary surface after landing on a planet. Competitors' robots are challenged to locate and identify objects, and then convey them to a base station. This activity is meant to be...
Semantic textual similarity measures the semantic equivalence between a pair of sentences. Lexical overlapping approach evaluates similarity among a sentence pair depending on the number of terms the sentence pair shares. The similarity can be measured at same level of abstraction or at multi levels. This paper presents the influence of token similarity measures using lexical overlap semantic similarity...
The number of users per cell is an important quantity in calculating various performance metrics in a cellular network. For a non-shadowing environment, while assuming a homogeneous Poisson point process for base station locations, the distribution of the number of users per cell has been derived using approximations for the distribution of the cell area. This approach does not extend to path-loss...
We propose a Riemannian quasi-Newton method to compute a geodesic invariant to scaling, translation, rotation and reparameterization and show that it is more efficient than the current state-of-the-art coordinate-descent/path-straightening approach.
High-quality depth data is needed in many advanced computer vision as well as 3D and virtual reality applications. To surpass the hardware limitations, computational approaches are commonly exploited, and the solutions are from the intersection of two fundamental problems, depth map super-resolution and inpainting, leading to a general problem of reconstructing depth data from a subset of samples...
This paper presents methods to compare high order networks using persistent homology. High order networks induce well-founded homological features and the difference between networks is measured by the difference between the homological features. This is a reasonable approximation to a valid metric in the space of high order networks modulo permutation isomorphisms. The approximations succeed in discriminating...
Extreme learning machine is state of art supervised machine learning technique for classification and regression. A single ELM classifier can however generate faulty or skewed results due to random initialization of weights between input and hidden layer. To overcome this instability problem ensemble methods can be employed. Ensemble methods may have problem of redundancy i.e. ensemble may contain...
Enterprise Resource Planning (ERF) systems are sophisticated information database that provide an automatic cross-functional business processes. An ERP user, however, often encounters challenges using complex ERP interfaces. Educational ERP implementation has been plagued with failure, but it to be adopted and is expanding in Indian higher education. An AICTE, UGC and others government approving bodies...
Subspace clustering has typically been approached as an unsupervised machine learning problem. However in several applications where the union of subspaces model is useful, it is also reasonable to assume you have access to a small number of labels. In this paper we investigate the benefit labeled data brings to the subspace clustering problem. We focus on incorporating labels into the k-subspaces...
A scheme to sample bandlimited graph signals in the presence of noise is analyzed. Samples are aggregated at a single node by successive applications of the so-called graph-shift operator that encodes the local structure of the underlying graph. In contrast to the noiseless case, when noise is present the choice of the sampling node and the local sample-selection scheme plays a major role in determining...
Realistic map data is the basis for meaningful simulation studies of Inter-Vehicle Communication (IVC) applications and protocols [1]. Synthetic scenarios such as isolated intersections or a perfectly laid-out grid do not feature the typical mix of low and high traffic density roads and can therefore not be used as a representative scenario for (sub)urban traffic [2].
Random instruction sequence (RIS) tools continue to be the main strategy for verifying and validating chip designs. In every RIS tool, test suites are created targeted to a particular functionality and run on the design. Coverage metrics provide us one mechanism to ensure and measure the completeness and thoroughness of these test suites and create new test suites directed towards unexplored areas...
We present a semi-supervised boosting algorithm for the multi-label classification by using the conditional label variance as a loss function over the unlabeled data. The experiments on the benchmark data sets show that the proposed algorithm outperforms its supervised counterpart as well as the existing information theoretic based semi-supervised methods, and its performance is steadily improving...
This paper considers the detection of possible deviation from a nominal distribution for continuously valued random variables. Specifically, under the null hypothesis, samples are distributed approximately according to a nominal distribution. Any significant departure from this nominal distribution constitutes the alternative hypothesis. It is established that for such deviation detection where the...
Identifying the source of network diffusion is an important task in applications such as epidemics management and understanding the trend propagation over social networks. As observing each node carries a cost, we study the problem of sequential selection of observed nodes from two aspects: which nodes to observe such that the source is localized with the lowest cost, and for a pre-specified number...
Design automation (DA) research has for over fifty years been performed in academia, semiconductor and system companies, and EDA companies worldwide. This research has been enabling to continued scaling of design productivity and growth of the semiconductor industry. For product companies, funding program managers and individual researchers alike, a highly relevant question is: what DA research, and...
News has, in this day and age, transformed primarily into a digital format with leading newspapers and news agencies having a significant online presence. The speed at which news reaches the reader notwithstanding, the proliferation of blogs and microblogs to deliver specialized content has become the order of the day. Even highly engaged users tend to disengage with a website when the content they...
Over the past decade, CMOS scaling has seen increasingly intrusive challenges from cost, variability, energy, reliability, and fundamental device-architectural and materials limitations. To maintain Moore's-Law scaling of integration value, the industry is urgently exploring beyond-silicon and beyond-CMOS device, interconnect and memory options, as well as heterogeneous, “More than Moore” integration...
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