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Research on the influence of specific hydrological environment change on current velocity and water exchange has a long history in oceanography; however, the majority of previous work has been based on traditional ocean models such as POM and FVCOM. This paper presents a stable joint method that combines a support vector machine with a hydrological model to predict current velocity in different hydrological...
Traffic lights recognition is important to make intelligent vehicles safe. Most of existing means to detect and recognize traffic lights focus on color, size and shape of traffic lights, which are great affected by weather and illumination conditions. In this work, we utilize deep learning and SVM classifiers to recognize traffic lights for varying illumination conditions. More specifically, a PCA...
A novel and efficient human action recognition method utilizing spatio-temporal interest point detector and 3D speed up robust features (3D SURF) descriptor is proposed. The spatio-temporal interest points are detected using two separate linear filters. Then 3D SURF descriptor is presented and demonstrated in detail to represent the local region around interest point. The experimental results on KTH...
Abstract -- In this paper we propose an evidential fusion approach to combining the decisions of text classifiers. These text classifiers are generated by four widely used learning algorithms: Support Vector Machine (SVM), kNN (Nearest Neighbour), kNN model-based approach (kNNM), and Rocchio on two text corpora. We first model each classifier output as a list of prioritized decisions and then divide...
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