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Topic evolution is an important research task for Topic Detection and Tracking (TDT), studying how the topics evolve over time on textual data. On the web forum, topics are often interactive, which means that new topics emerge and old ones decay and the number of topics is always in a dynamic change. This paper presents an on-line adaptive topic evolution model based on Latent Dirichlet Allocation...
In the field of computer vision, image matching is very important in many applications, such as the object recognition, 3D reconstruction, stereo vision, motion tracking and augmented reality. A method of improving the Opensurf algorithm used in AR for decreasing matching points and mismatch and increasing the calculation speed is proposed.
The -constrained minimal singular value of the sensing matrix for sparse signal recovery is investigated in this letter. By exploiting certain geometrical properties of the , we derive new sufficient conditions for the recovery of both exactly and approximately sparse signals. Moreover, we demonstrate that a class of structured random matrices, including...
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