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Text detection in natural images remains a very challenging task. For instance, in an urban context, the detection is very difficult due to large variations in terms of shape, size, color, orientation, and the image may be blurred or have irregular illumination, etc. In this paper, we describe a robust and accurate multiresolution approach to detect and classify text regions in such scenarios. Based...
Location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform comprehensive analysis of all protein location patterns, automated methods are needed. With the goal of extending automated subcellular location pattern analysis methods to high resolution images of tissues, 3D confocal microscope images of polarized CaCo2 cells immunostained...
K-nearest neighbor (KNN) is a common classification method for data mining techniques. It has been widely used in many fields because of the implementation simplicity, the clarity of theory and the excellent classification performance. But KNN will increase classification error rate when training samples distribute unevenly or sample number of each class is very different. So, learning from the idea...
Optimizing vision processing is crucial for real-time performance of robots in RoboCuppsilas small-size league (SSL). We describe in this paper our current approach to improve visual processing in ITAMpsilas Eagle Knights SSL team. We describe our use of a neural network to classify camera image pixels to a discrete set of color classes that is robust under different light conditions. We show how...
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