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The high-level feature representation of deep convo-lutional neural networks (ConvNets) has proven to be superior to hand-crafted low-level features. Thus, this study investigates the effect of fusing such high-level features from multi-deep ConvNets under an application of visual object/scene categorization. In which, three pre-trained ConvNets are exploited as feature extractors, a single hidden...
In this paper, a novel quantum fuzzy particle swarm optimization (QFPSO) approach has been proposed for image clustering. The particle swarm optimization is used to search the global optimal clustering center. Moreover, the quantum encoding is introduced and the quantum operation is implemented on each particle to overcome the premature convergence problem effectively. The experimental results showed...
A critical component of today's commercial search engines is an advertisement platform. The current state-of-the-art of such platforms is primarily based on advanced keyword matching to determine the relevance of advertisements for users' queries. However, such keyword matching techniques suffer from missing user intent when the query domain is visual as opposed to textual. To handle such a domain,...
An efficient algorithm for facial features extractions is proposed. The facial features we extracted are the edges of two eyes, nose and mouth. The algorithm is based on an improved Gabor wavelets edge detector to detect the face region and facial features regions. The experimental results show that the proposed method is robust against facial expression, illumination, and can be also effect if the...
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