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Learning salient representations of multiview data is an essential step in many applications such as image classification, retrieval, and annotation. Standard predictive methods, such as support vector machines, often directly use all the features available without taking into consideration the presence of distinct views and the resultant view dependencies,(More)
Almost all of the current top-performing object detection networks employ region proposals to guide the search for object instances. State-of-the-art region proposal methods usually need several thousand proposals to get high recall, thus hurting the detection efficiency. Although the latest Region Proposal Network method gets promising detection accuracy(More)
This paper addresses the path control problem for a ship steering in restricted waters using sliding mode techniques. The ship’s dynamic equations and numerical computation of the bank disturbance forces are briefly described. The ship’s path control system is presented which leads to a nonminimum phase system. Therefore, the traditional input–output(More)
In this paper, we try to address the joint optimization problem of the extreme learning machines corresponding to different features. The method is based on the L 2,1 norm penalty, which encourages joint sparse coding. By adopting such a technology, the intrinsic relation between different features can be sufficiently preserved. To tackle the problem that(More)
A neural network (NN)-based adaptive controller with an observer is proposed for the trajectory tracking of robotic manipulators with unknown dynamics nonlinearities. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity, while NNs are employed to further(More)
The classification of high-dimensional data with too few labeled samples is a major challenge which is difficult to meet unless some special characteristics of the data can be exploited. In remote sensing, the problem is particularly serious because of the difficulty and cost factors involved in assignment of labels to high-dimensional samples. In this(More)