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Neural networks methodology is a tool to get potential energy surface (PES) in cases where there is too much dispersion of data; hence, a binding energy fitting can be found with this methodology on asphaltene-asphaltene molecular interaction. A data distribution of intermolecular pair potential (UAA) interaction in a vacuum between two molecular asphaltenes systems using compass classical force field...
This paper presents work towards recognizing facial expressions that are used in sign language recognition. Facial features are tracked to effectively capture temporal visual cues on the signer's face during signing. A Bayesian framework is proposed as a feedback mechanism to the Kanade-Lucas-Tomasi (KLT) tracker for reliably tracking facial features in the presence of head motions and temporary occlusions...
This paper presents an improved active shape model algorithm, that exploits auto associative neural networks (AANNs) to estimate the local feature models. The proposed technique aims at solving face feature localization tasks, nevertheless it can be used also in the more general case of object detection. Three main contributions are presented. The first one consists in the estimation of elliptic search...
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