Motivated by the fact that a great deal of information is closely related to spatial location, a new type of skyline queries, location-dependent skyline query (LDSQ), was recently presented. Different from the convent...
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It's well known machine learning from examples is an effective method to solve non-linear classification problem. A new dynamic method of machine learning from transition example is given in this paper. This metho...
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The evolution of social network and multimedia technologies encourage more and more people to generate and upload visual information, which leads to the generation of large-scale video data. Therefore, preeminent comp...
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The evolution of social network and multimedia technologies encourage more and more people to generate and upload visual information, which leads to the generation of large-scale video data. Therefore, preeminent compression technologies are highly desired to facilitate the storage and transmission of these tremendous video data for a wide variety of applications. In this paper, a systematic review of the recent advances for large-scale video compression (LSVC) is presented. Specifically, fast video coding algorithms and effective models to improve video compression efficiency are introduced in detail, since coding complexity and compression efficiency are two important factors to evaluate video coding approaches. Finally, the challenges and fu- ture research trends for LSVC are discussed.
While tracing objects or analyzing human activities with RFID data sets, the quality of RFID data is a crucial aspect. The raw RFID data streams, however, tend to be noisy, including missed readings and unreliable rea...
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A large mode area multi-core orbital angular momentum(OAM)transmission fiber is designed and optimized by neural network and optimization *** neural network model has been established first to predict the optical prop...
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A large mode area multi-core orbital angular momentum(OAM)transmission fiber is designed and optimized by neural network and optimization *** neural network model has been established first to predict the optical properties of multi-core OAM transmission fibers with high accuracy and speed,including mode area,nonlinear coefficient,purity,dispersion,and effective index *** the trained neural network model is combined with different particle swarm optimization(PSO)algorithms for automatic iterative optimization of multi-core structures *** to the structural advantages of multi-core fiber and the automatic optimization process,we designed a number of multi-core structures with high OAM mode purity(>95%)and ultra-large mode area(>3000µm^(2)),which is larger by more than an order of magnitude compared to the conventional ring-core OAM transmission fibers.
In recent years, the deep learning method has been widely used in the financial field, promoting the development of stock price forecasting. The time series data in reality has complex characteristics, and the traditi...
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作者:
Han, FeiZhang, YaoZhao, MengTianjin University of Technology
Engineering Research Center of Learning-Based Intelligent System Ministry of Education Key Laboratory of Computer Vision and System of Ministry of Education Tianjin300384 China
As an emerging distributed machine learning paradigm, federated learning (FL) only shares model updates between clients and servers, and training data are secured on each client's device. Due to local data privacy...
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Point-of-Interest is an interesting research topic of personalized recommendation. In this paper, a new position-based recommendation framework is proposing by using the time attribute. We establish a user matrix with...
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This paper puts forward a visual method of detecting pop-cans based on AdaBoost Algorithm. This method, is basing on the idea of AdaBoost Algorithm, and we use Haar Feature and LBP Feature to extract pop-can character...
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After Mountcastle proposed the theory that all parts of mammalian neocortex are uniform [1], more and more evidences were found to prove that no matter what function the field of neocortex provide, the organizing of c...
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