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Hyperspectral image (HSI) classification is a popular yet challenging research topic in the remote sensing community. This letter attempts to encode both spectral and spatial information into deep features for HSI classification. We first propose a semisupervised method for training the stacked autoencoder to obtain discriminative deep features. A batch training scheme is introduced to constrain the...
With the appearance and development of the technology of malicious codes and other unknown threats, information security has drawn people's attention. In this paper, we investigate on behavior-based detection which is different from traditional static detection technology. Firstly, we discuss the procedure in detail, especially feature extraction and classification. Several machine learning methods...
The limited underwater observation scenarios pose great challenges to the problem of object recognition from the low-resolution underwater images. This paper proposes a framework to explicitly learn the discriminative features from relatively low resolution images, by resorting to deep learning approaches and super-resolution method. Firstly, the framework tackles the problem of limited discriminative...
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...
Most current three-dimensional reconstruction methods often require at least two or more input images to reconstruct the shape of the object. Traditionally, it is hard to reconstruct the 3D shape only from one single input image. In this paper, we propose an effective method to reconstruct the 3D texture surface from a single input image for the texture with similar appearances and reflectance properties...
The Extreme Learning Machine algorithm was proposed by Prof. Guangbin Huang in 2004. It is a single hidden layer feedforward neural network. It has attracted extensive research of many scholars because of its fast speed, simple implementation and good generalization performance. In this paper, Quantum Particle Swarm Optimization was introduced to extreme learning machine to solve the problem of complex...
BP algorithm can be applied in comprehensive evaluation. A hybrid neural network based on the combination of GA and BP algorithms is proposed. The algorithm made fully use of GA's global searching to improve the learning ability of BP neural network. Then, the method is used in comprehensive evaluation, which the genetic algorithm can improve the weights of the neural network and enhance the training...
Web based data integration systems run in an unpredictable and dynamic environment, which makes the traditional query processing approach inapplicable. Problems necessitating AQP (Adaptive Query Processing) techniques include: (1) statistics may be insufficient; (2) statistics may be imprecise; (3) unavailable data sources may make query results incomplete. In this paper, we present a novel data integration...
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