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A Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model (GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model (HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic...
This paper proposes a method of predicting future medical examination measurements given the past values. The medical examinations considered in this paper are blood sugar level, low and high blood pressures, and cholesterol level. This paper uses a specific type of artificial neural networks, radial-basis function network (RBFN), to approximate mapping from the past medical measurements to that of...
This paper investigates various emotion recognition techniques from the facial expression of human subjects. To describe human facial expressions, a number of characteristic points are extracted from input face images using active shape models (ASMs), and translated 49 scalar features so that they are invariant to scale and position changes. The scalar feature values then construct a 49-dimensional...
To make it viable for remote monitoring to scale to large patient populations, the accuracy of detectors used to identify patient states of interests must improve. Patient-specific detectors hold the promise of higher accuracy than generic detectors, but the need to train these detectors individually for each patient using expert labeled data limits their scalability. We explore a solution to this...
Spatial resolutions of IKONOS high-resolution panchromatic (PAN) and low-resolution multispectral (MS) satellite images are 1 m and 4 m, respectively. To cope with color distortion and blocking artifacts in fused images, in this study, a new IKONOS imagery fusion approach using particle swarm optimization (PSO) is proposed. The pixels of fused images in the training set are classified into several...
In this study, a new edge-directed image interpolation approach using visual attention model and particle swarm optimization (PSO) is proposed. First, a high-quality saliency map of an image to be interpolated is generated by the proposed visual attention model in an effective manner. Then, based on the saliency map, bilinear interpolation and the proposed PSO interpolation are employed for non-saliency...
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