• Citations Per Year
Learn More
Our team from the JHU HLTCOE and the University of Maryland submitted runs for all three variants of the TACKBP entity linking task. For the monolingual tasks, we essentially mirrored our HLTCOE TAC-KBP 2010 submission, making only modest changes to accommodate differences in 2011, namely the requirement to cluster NIL responses, and the change in(More)
Prostate segmentation in MRI may be difficult at the interface with the bladder where the contrast is poor. Coupled-models that segment simultaneously both organs with non-overlapping constraints offer a good solution. As a pre-segmentation of the structures of interest is required, we propose in this paper a fast deformable model to segment the bladder.(More)
Considering the disadvantages of the distribution system, which is made of the rotating machine and the mechanical transmission device, such as low positioning accuracy, vulnerable to load influence, this paper puts forward a new kind of distribution system consists of the permanent magnet linear synchronous motor (PMLSM), which is based on the fuzzy(More)
Remote sensing images contain a lot of mixed image pixels, but it is difficult to classify these pixels. If the number of pixel’s end-member is regarded as unchangeable, the traditional pixel unmixing algorithm cannot get a good result. In this paper we develop a new method of selective end-members for pixel unmixing based on the fuzzy ARTMAP neural(More)
As the spatial resolution of hyperspectral imagery is usually limited, sub-pixel targets only occupy part of the pixel area. Unstructured detectors, such as adaptive cosine estimate (ACE), has shown promising performance in sub-pixel targets detection, which models the background with a distribution property. This paper proposes a unstructured detector in(More)
In a classification problem, we are given the input x and want to find out which category it belongs to in a given label set Π. Information from the input x is often represented as a feature vector φ(x). The basic idea of linear classifiers, then, is to have a weight vector wz for each class label z, in the same dimension as φ(x), to distinguish input from(More)
It is well known that the symplectic algorithm for the finite dimensional Hamiltonian systems are very powerful and successful in numerical calculations in comparison with other various non-symplectic computational schemes since the symplectic schemes preserve the symplectic structure in certain sense. On the other hand, the Lagrangian formalism is quite(More)