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Deep learning techniques achieve state-of-the-art performance on many computer vision related tasks, e.g. large-scale object recognition. In this paper we show that recognition accuracy degrades when used in daily mobile scenarios due to context variations caused by different locations, time of a day, etc. To solve this problem, we present DeepCham - the first adaptive mobile object recognition framework...
Traditionally, content-based image retrieval systems (CBIR) are designed to allow users to search for images in large databases which match closely with users' query images. Recent emergence of powerful mobile devices equipped with digital cameras have led to the emergence of several interesting mobile CBIR applications. Due to the limited resources in mobile devices, it is critical that the image...
Number identification of maintenance equipment is an emergent problem of support resources deployment for aircraft in design and development phase. Taking maintenance mission requirements as input, queuing model of batch arrival LRU (Line Replaceable Units) based on Queuing Theory is constructed. Effects of maintenance equipment failure on queuing model are analyzed. Being subjected to the constraint...
In this paper, a new pruning algorithm based on grey incidence analysis for feedforward neural networks is presented.The pruned network has the optimal topology with avoiding over training and obtaining good generalization.The removed connections and the incorporated connections are chosen according to the degree of grey incidence of each output sequence of the network units. The simulation results...
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