Pi-Fuei Hsieh

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................................................................................................................... v CHAPTER 1: INTRODUCTION .................................................................................. 1 1.1 Background ................................................................................................... 1 1.2 Statement(More)
A parametric linear feature extraction method is proposed for multiclass classification. The skeleton of the proposed method consists of two types of schemes that are complementary to each other with regard to the discriminant information used. The approximate pairwise accuracy criterion (aPAC) and the common-mean feature extraction (CMFE) are chosen to(More)
Hyperspectral data potentially contain more information than multispectral data because of higher dimensionality. Information extraction algorithm performance is strongly related to the quantitative precision with which the desired classes are defined, a characteristic which increases rapidly with dimensionality. Due to the limited number of training(More)
In remote sensing, the number of training samples is often limited. For hyperspectral data, it becomes more difficult to obtain accurate estimates of class statistics because of the small ratio of the training sample size to dimensionality. Generally speaking, classification performance depends on four factors: class separability, the training sample size,(More)
We have developed a system that recognizes the facial expressions in Taiwanese Sign Language (TSL) using a phoneme-based strategy. A facial expression is decomposed into three facial phonemes, including eyebrow, eye, and mouth. A fast method is proposed for locating the areas facial phonemes. The shapes of the phonemes were then matched by the deformable(More)
Linear feature extraction methods have been widely used to remove redundant features and to speed up data processing. The limitations regarding the preservation of class discrimination are shown when classes are originally separated by nonlinear decision boundaries. Recently, nonlinear kernel-based feature extraction algorithms have shown a potential in(More)
In multisource classification, the logarithmic opinion pool (LOGP) mechanism is a widely used approach to decision fusion. The key problem of the LOGP mechanism is how to estimate the weights of the probabilities associated with various sources and classes. The weights used in the proposed method are associated with the source-wise as well as the class-wise(More)