Karthik Ganesan Pillai

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Change detection from remote sensing imagery is of great interest in disaster management, surveillance, and other applications. Most of the existing approaches are pixel based and rely on direct comparison of radiometric values to detect changes. Such techniques are susceptible to atmospheric conditions, noise, and registration errors. In this paper, we(More)
Oral submucous fibrosis (OSMF) is a crippling disease that impedes the normal functions of the oral cavity. It is a slowly progressive disease characterized by epithelial atrophy, abnormal accumulation of collagen fibres in the sub-epithelial tissues leading to severe restriction of mouth opening and movement of the tongue. The disease is believed to be a(More)
This paper introduces a new public benchmark dataset of solar image data from the Solar Dynamics Observatory (SDO) mission. This is the first release, which contains over 15,000 images and nearly 24,000 solar events, spanning the first six months of 2012. It combines region-based event labels from six automated detection modules, ten pre-computed image(More)
Spatiotemporal co-occurrence patterns (STCOPs) represent the subsets of event types that occur together in both space and time. However, the discovery of STCOPs in data sets with extended spatial representations that evolve over time is computationally expensive because of the necessity to calculate interest measures to assess the co-occurrence strength,(More)
OBJECTIVES A study was undertaken to assess the prevalence of taurodontism in premolars in a group of adult dental patients in Trinidad and Tobago since there is no such data available for the region. METHODS Periapical and orthopantomograms of 1090 randomly selected patients were examined for the presence of an apically displaced pulp chamber without the(More)
Spatio-temporal co-occurring patterns represent subsets of event types that occur together in both space and time. In comparison to previous work in this field, we present a general framework to identify spatio-temporal co occurring patterns for continuously evolving spatio-temporal events that have polygon-like representations. We also propose a set of(More)
A novel swarm-based algorithm is proposed for the training of artificial neural networks. Training of such networks is a difficult problem that requires an effective search algorithm to find optimal weight values. While gradient-based methods, such as backpropagation, are frequently used to train multilayer feedforward neural networks, such methods may not(More)
A novel overlapping swarm intelligence algorithm is introduced to train the weights of an artificial neural network. Training a neural network is a difficult task that requires an effective search methodology to compute the weights along the edges of a network. The backpropagation algorithm, a gradient based method, is frequently used to train multilayer(More)
In this paper, we investigate using specifically-designated spatiotemporal indexing techniques for mining cooccurrence patterns from spatiotemporal datasets with evolving polygon-based representations. Previously, suggested techniques for spatiotemporal pattern mining algorithms did not take spatiotemporal indexing techniques into account. We present a new(More)