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This contribution presents a method for automatic detection of excitatory, asymmetric synapses and segmentation of synaptic junctional complexes in stacks of serial electron microscopy images with nearly isotropic resolution. The method uses a Random Forest classifier in the space of generic image features, computed directly in the 3D neighborhoods of each pixel, and an additional step of interactive...
For any autonomous system it is very important to acquire the knowledge of the surrounding environment. Images and videos acquired by the vision based sensors can provide meaningful information about the environment, which can be very useful for the navigation of autonomous system like mobile robots. To extract road information from image frames for navigation purpose they have to be classified. Classification...
Fully automated image segmentation is an essential step for designing automated identification systems. This paper investigates the problem of real-time image segmentation in the context of ear biometrics. The proposed approach is based on Haar features arranged in a cascaded Adaboost classifier. This method, widely known as Viola-Jones in the context of face detection, has a limitation of an extremely...
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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