Jiamin Xu

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Text detection and recognition is a challenging problem methods degrades drastically [4,5) because of the variations in edge in document analysis due to the presence of the unpredictable nature pattern and strength. For instance, In Figure I, (a) shows 2D characters of video texts, such as the variations of orientation, font and size, chosen from video, (b)(More)
—Achieving good accuracy for text detection and recognition is a challenging and interesting problem in the field of video document analysis because of the presences of both graphics text that has good clarity and scene text that is unpredictable in video frames. Therefore, in this paper, we present a novel method for classifying graphics texts and scene(More)
The two-dipole model of theta generation in hippocampal CA1 suggests that the inhibitory perisomatic theta dipole is generated by local GABAergic interneurons. Various CA1 interneurons fire preferentially at different theta phases, raising the question of how these theta-locked interneurons contribute to the generation of theta oscillations. We here(More)
Text detection and recognition in video is challenging due to the presence of different types of texts, namely, graphics (video caption), scene (natural text), 2D, 3D, static and dynamic texts. Developing a universal method that works well for all these types is hard. In this paper, we propose a novel method for classifying graphics-scene and 2D-3D texts in(More)
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