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Medical data classification is a prime data mining problem being discussed about for a decade that has attracted several researchers around the world. Most classifiers are designed so as to learn from the data itself using a training process, because complete expert knowledge to determine classifier parameters is impracticable. This paper proposes a hybrid(More)
This paper analyzes various earlier approaches for selection of hidden neuron numbers in artificial neural networks and proposes a novel criterion to select the hidden neuron numbers in improved back propagation networks for wind speed forecasting application. Either over fitting or under fitting problem is caused because of the random selection of hidden(More)
Since usage of digital video is wide spread nowadays, quality considerations have become essential, and industry demand for video quality measurement is rising. This proposal provides a method of perceptual quality assessment in H.264 standard encoder using objective modeling. For this purpose, quality impairments are calculated and a model is developed to(More)
  • Corresponding Author, K Kothavari, K Kothavari, S N Deepa
  • 2014
This paper presents a Computer Aided Detection method in Computed Tomography (CT) images of lungs using mathematical morphological operations, Early detection and treatment of lung cancer can greatly improve the survival rate of patient. Segmentation is one of the important step in analysing medical images, RASM segmentation is carried out in this paper.(More)