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This paper proposes to use multilevel ROI-based features and machine learning method to improve the accuracy of qualitative recognition of mild cognitive disorder in parkinsonism. 77 Parkinson's patients and 32 normal controls with neuropsychological assessments and structural magnetic resonance images from the Parkinson's Progression Markers Initiative dataset are tested. Specifically, the BrainLab...
In this paper, we present a novel interactive image segmentation technique that automatically learns segmentation parameters tailored for each and every image. Unlike existing work, our method does not require any offline parameter tuning or training stage, and is capable of determining image-specific parameters according to some simple user interactions with the target image. We formulate the segmentation...
This paper analyzes the pick-and-place process of the flip-chip technology, addressing two different control goals. Iterative learning control (ILC) is adopted to enhance the point-to-point positioning accuracy in the IC chip picking procedure. Furthermore, a trajectory modification is proposed for the traditional soft landing process, hence improving the efficiency of the IC chip placing procedure...
In this paper, we report the research of iterative learning control method on linear voice coli motor and application in flip chip. As the flip chip technology has realized minimum size package, excellent electric performance and thermal characteristics, it is suitable for mass production and high-density package. The process usually includes two different kinds of movement under the high speed and...
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