In order to better monitor and manage the signal transmission in the communication system and base station, and carrier detection is more effective. This paper designs a carrier(Carrier frequency) detection system bas...
In order to better monitor and manage the signal transmission in the communication system and base station, and carrier detection is more effective. This paper designs a carrier(Carrier frequency) detection system based on FPGA, including system design requirements, FPGA selection, system framework design, carrier detection method design and so on. The performance indexes of the system are tested, such as carrier frequency range, carrier search time, carrier detection number and CPU consumption rate. The system has the advantages of high flexibility and good portability, and has a good application prospect in communication system, base station and other equipment.
Simultaneous Localization and Mapping is an important technology which help a mobile robot to determine its location and build the environment map. Recently, the RGBD sensor is widely used in the robot, research on RG...
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ISBN:
(纸本)9781509064151;9781509064144
Simultaneous Localization and Mapping is an important technology which help a mobile robot to determine its location and build the environment map. Recently, the RGBD sensor is widely used in the robot, research on RGBD-SLAM becomes a hot topic. In order to calculate the movement parameters of robot, feature matching is adopted to register the two adjacent RGBD images in the video stream. This paper proposed an improved feature matching method for RGBDSLAM. The experiment results show that, compared with the traditional SIFT feature matching methods for RGBD-SLAM,the performance of the proposed method is improved significantly.
As a key task in the process of natural language understanding,semantic role labeling has been widely used in the field of natural language processing at a higher level,such as information extraction,text analysis and...
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As a key task in the process of natural language understanding,semantic role labeling has been widely used in the field of natural language processing at a higher level,such as information extraction,text analysis and machine *** paper adopts the current mainstream semantic character annotation method based on syntactic tree analysis,proposes a Chinese semantic role labeling method that integrates hierarchical syntactic cues,and implements a hierarchical annotation model based on conditional random field *** the basis of the model,the influence of different syntactic features on system performance is *** feature sets are formulated for verb predicate and noun predicate respectively,and the contribution of each feature to the system is *** experimental results show that the introduction of phrase syntax analysis can effectively improve the recognition effect of semantic *** results obtained in this study have a good reference value for future research.
Aimed at the problem that traditional histogram is sensitive to illumination changes in visual tracking, combined with the CN(Color Name) feature, we proposed a new feature(denotes CNH, Color Name Histogram) based on ...
Aimed at the problem that traditional histogram is sensitive to illumination changes in visual tracking, combined with the CN(Color Name) feature, we proposed a new feature(denotes CNH, Color Name Histogram) based on color name. Firstly, the method projected the original RGB image to CN space to obtain robust 11 feature layers. Then, we counted the each pixel numbers of feature layers. Finally, normalizing the amount of pixels in each layer. In addition, we adopted a feature adaptive fusion method to combine CNH and HOG(Histogram of Oriented Gradient). In order to prove validity of the proposed algorithm, we use Staple(Sum of Template And Pixel-wise Learners) algorithm frame to make a controlled trial. In contrast with the reference algorithms, the success of our algorithm increases by 1.5% and the precision increases by 1.7%. The results show that this method retains the advantages of traditional histogram which is insensitive to target deformation, but also enhances the robustness to illumination change.
For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of inter...
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For the polarimetric synthetic aperture radar interferometry (PoIInSAR) processing, it is necessary to coregister all the images, including the coregistration of polarimetric SAR images and the coregistration of interferometric SAR images. Otherwise, the performance of the estimated optimal interferograms will be deteriorated. A generalized scattering vector (GSV) model is proposed to execute the PoIInSAR optimal interferograms estimation. The generalized scattering vector is constructed by the Pauli scattering vectors of the processing pixel and the surrounding pixels. Even though there are coregistration errors, all the polarimetric information of the current processing pixel is entirely included in the generalized scattering vector. Therefore, the GSV-based method can automatically recover the optimal scattering mechanisms of the processing pixel with coregistration errors either in interferoemetric channels or polarimetric channels. Theoretical analysis and processing results of simulated PoISARPro data and real PALSAR data validate the effectiveness and correctness of the proposed method.
Aiming at the current situation of poor quality of artificial intelligence teaching and weak students' interest in learning, a case teaching method is proposed. This paper analyzes the teaching status of artificia...
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Aiming at the current situation of poor quality of artificial intelligence teaching and weak students' interest in learning, a case teaching method is proposed. This paper analyzes the teaching status of artificial intelligence firstly, and then systematically describes the case teaching method. Finally, the necessity of introducing case teaching method into artificial intelligence teaching is studied. Practice shows that the case teaching method can effectively enhance students' self-learning ability, improve students' comprehensive innovation ability, and promote the development of artificial intelligence teaching.
MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely avai...
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MicroRNAs( miRNAs) are reported to be associated with various diseases. The identification of disease-related miRNAs would be beneficial to the disease diagnosis and prognosis. However,in contrast with the widely available expression profiling, the limited knowledge of molecular function restrict the development of previous methods based on network similarity measure. To construct reliable training data,the decision fusion method is used to prioritize the results of existing methods. After that,the performance of decision fusion method is validated. Furthermore,in consideration of the long range dependencies of successive expression values,Hidden Conditional Random Field model( HCRF) is selected and applied to miRNA expression profiling to infer disease-associated miRNAs. The results show that HCRF achieves superior performance and outperforms the previous methods. The results also demonstrate the power of using expression profiling for discovering disease-associated miRNAs.
Reductions of the self-consistent mean field theory model of amphiphilic molecules in solvent can lead to a singular family of functionalized Cahn-Hilliard (FCH) energies. We modify these energies, mollifying the sing...
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Parallax handing is a challenging problem for image stitching. Optimal seam line method is employed in this paper to deal with the misalignment on panoramas caused by parallax problem. It's an important method for...
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Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring ...
Due to the limitation of hardware resources, the traditional people flow monitoring system based on computer vision in public places can't meet different crowd-scale scenarios. Therefore, a people flow monitoring system based on MD-MCNN algorithm is designed, which is an application system combining the improved SSD object detection algorithm MNSSD and MCNN density map regression algorithm. In the initial stage, the system uses MNSSD for accurate detection and counting. If the people flow gradually reaches a certain threshold, the system automatically uses MCNN to estimate people flow until the people flow falls below the threshold. Through the experimental verification, the system can realize the people flow statistics of low-density and high-density people in different scenarios, and can be applied on the existing embedded platform. This scheme can be extended to smart cities, smart scenic spots, smart transportation and other fields.
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