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In order to improve the traditional Particle Swarm Optimization (PSO) algorithm's speed and optimization ability, this paper proposes a new algorithm based on CUDA (Compute Unified Device Architecture) technology which employs the two level PSO, the bottom level PSO and the top level PSO. And in the bottom level, the particles are divided into N groups, each of which will run the PSO and send the...
Scene classification aims to group images into semantic categories. It is a challenging problem in computer vision due to the difficulties of intra-class variability and inter-class similarity. In this paper, a scene classification approach based on single-layer sparse autoencoder (SAE) and support vector machine (SVM) is proposed. This approach consists of two steps: SAE-based feature learning step...
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