Global ETD Search
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Showing 1 to 8 of 8 for “"SVM regression"”.
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Towards trainable man-machine interfaces : combining top-down constraints with bottom-up learning in facial analysis
… learning method based on support vector machine (SVM) regression for estimating the parameters of LMMs directly from pixel-based representations of faces. We combine these methods for designing new, more self-contained systems for recognizing facial expressions, estimating facial pose and for …
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USE OF LANGUAGE TECHNOLOGY TO IMPROVE MATCHING AND RETRIEVAL IN TRANSLATION MEMORY
… is presented, where a Support Vector Machine (SVM) regression model is trained, which calculates the similarity between two segments. The approach based on manually designed features did not retrieve better matches than simple edit-distance. Two approaches for retrieving segments from a TM …
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Fast Magnetic Resonance Imaging by Data Sharing: Generalized Series Imaging and Parallel Imaging
… model more accurate. A support vector machine (SVM) regression method is developed to overcome the ill-conditioning of the model matrix. An adaptive scheme for choosing the regularization parameters is also proposed. Experimental results show that the proposed algorithm can reconstruct images …
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Application of Computational Intelligence in Cognitive Radio Network for Efficient Spectrum Utilization, and Speech Therapy
… using optimized ANN and support vector machine (SVM) regression models for prediction of real world RF power. The prediction accuracy and generalization was improved by combining different prediction models with a weighted output to form one model. The meta-parameters of the prediction models …
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Machine Learning Models in Fullerene/Metallofullerene Chromatography Studies
Machine learning methods are now extensively applied in various scientific research areas to make models. Unlike regular models, machine learning based models use a data-driven approach. Machine learning algorithms can learn knowledge that are hard to be recognized, from available data. The …
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Advances in medical infrared thermography
… developed a framework based on Gaussian Process Regression (GPR) with LOSO cross-validation to correlate the thermal features with the corresponding ABI. Additionally, we proposed a classification model based on the weighted K-Nearest neighbors (WKNN) algorithm to assess the severity of PAD based …