Learn More
In this paper, we introduce a new approach to fingerprint classification based on both singularities and traced pseudoridge analysis. Since noise exists in most of the fingerprint images including those in the NIST databases which are used by many researchers, it is difficult to get the correct number and position of the singulairities such as core or delta(More)
Fluorescence microscope images capture information from an entire field of view, which often comprises several cells scattered on the slide. We have previously trained classifiers to accurately predict subcellular location patterns by using numerical features calculated from manually cropped 2D single-cell images. We describe here results on directly(More)
This paper addresses a general class of capacity planning problems under uncertainty , which arises, for example, in semiconductor tool purchase planning. Using a scenario tree to model the evolution of the uncertainties, we develop a multi-stage stochastic integer programming formulation for the problem. In contrast to earlier two-stage approaches, the(More)
System-level design methodologies have been introduced as a solution to handle the design complexity of embedded multiprocessor SoC (MPSoC) systems. In this paper we describe a system-level design flow starting from Simulink specification, focusing on concurrent hardware and software design and verification at four different abstraction levels: Simulink(More)
Applications based on electrocardiogram (ECG) signal feature extraction and classification are of major importance to the autodiagnosis of heart diseases. Most studies on ECG classification methods have targeted only 1-or 2-lead ECG signals. This limitation results from the unavailability of real clinical 12-lead ECG data, which would help train the(More)