This paper focuses on matching 1D structures by variational methods. We provide rigorous rules for the construction of the cost function, on the basis of an analysis of properties ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Principal Component Analysis (PCA) is a well-established technique in image processing and pattern recognition. Incremental PCA and robust PCA are two interesting problems with nu...
Yongmin Li Li, Li-Qun Xu, Jason Morphett, Richard ...
In this paper, we study the interdependency between leakage energy and chip temperature in real-time systems. We observe that the temperature variation on chip has a large impact ...
Methods for controlling the adaptation process of an on-line handwritten character recognizer are studied. The classifier is based on the -nearest neighbor rule and it is adapted...
Vuokko Vuori, Jorma Laaksonen, Erkki Oja, Jari Kan...