Many major cities suffer from severe traffic congestion. Road expansion in the cites is usually infeasible, and an alternative way to alleviate traffic congestion is to coordinate the route of vehicles. Various path s...
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The user's filtering costs and time costs were increased because of a large number of search results in the context of big data technology. Therefore, personalized recommendation technology is needed to improve th...
The user's filtering costs and time costs were increased because of a large number of search results in the context of big data technology. Therefore, personalized recommendation technology is needed to improve the utilization ratio of information resources, which carries out accurate and efficient information filtering. This paper focuses on the employment recommendation algorithm hoping to maximize the true intention of job applicants in the recommended job list. As an important tool in machine learning, ensemble learning can improve the prediction accuracy and adaptability effectively in job recommendation algorithms. The main work of this paper is to carry out some research on the algorithm concept related to recommendation algorithm and gradient promotion decision tree algorithm based on recommendation algorithm, and build an employment recommendation algorithm. The employment recommendation algorithm is evaluated by the TOPN list experiment.
The problem of fault detection capability of combinatorial testing has drawn a lot of attention. People conducted many experiments on different subjects to compare fault detection capabilities of combinatorial testing...
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Classification of a hyperspectral image (HSI) is a very active topic in remote sensing, which has practical applications in many fields, In this paper, a multitask sparse logistic regression method based on multi-feat...
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Classification of a hyperspectral image (HSI) is a very active topic in remote sensing, which has practical applications in many fields, In this paper, a multitask sparse logistic regression method based on multi-feature and decision fusion approach (MTSLR-MPGF) is proposed for cross-scene hyperspectral image classification. Specifically, the Gabor Features with certain orientations and morphology feature are utilized and used for hyperspectral imagery classification. Next, we used feature fusion methods in order to produce an accurate thematic map based on the remote sensed hyperspectral image classification. The extensive experiments on two real hyperspectral data sets have demonstrated superior performance of the proposed MTSLR-MPGF approach over the state-of-the-art methods in terms of overall accuracy and average accuracy.
Estimating depth from RGB images can facilitate many photometric computer vision tasks, such as indoor localization, height estimation, and simultaneous localization and mapping (SLAM). Recently, monocular depth estim...
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We present a new method for improving the performances of variational autoencoder (VAE). In addition to enforcing the deep feature consistent principle thus ensuring the VAE output and its corresponding input images t...
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A Natural Language Interface (NLI) facilitates users to pose queries to retrieve information from a database without using any artificial language such as the Structured Query Language (SQL). Several applications in v...
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We propose an application of the transfer learning strategy of VGG16 to lung cancer CT diagnosis and conduct the experiment to clarify the performance of detection. Contributions of this paper are following three work...
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With the development of the Internet of Vehicles, the application of Advanced Driver Assistance Systems(ADAS) is becoming more and more extensive. As one of ADAS, Adaptive Cruise Control(ACC) technology has been widel...
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Researchers are devising new ways for robust digital content delivery in situations where telecommunication signal strength is very low, especially during natural disasters. In this paper, we present research work tar...
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