“移动镜头”和“长镜头”——试论李白山水诗的取象特征

李白的山水诗境界开阔,飘逸流转。这种审美特征的形成,离不开李白独特的取象方式。借鉴影视镜头理论来看,李白的山水诗常常使用"移动镜头"和"长镜头"取象,因而山水景物富于动感、完整连贯,并表现出强烈的主观感情色彩。"我"为主而山水为从,无限风景眼前流过;"以我观群动,以动开万境"。王世贞所言"太白佳境"恰是运用"长镜头"和"移动镜头"取象法所产生的境界。

Establishing and validating a spotted tongue recognition and extraction model based on multiscale convolutional neural network

Objective In tongue diagnosis,the location,color,and distribution of spots can be used to speculate on the viscera and severity of the heat evil.This work focuses on the image analysis method of artificial intelligence(AI)to study the spotted tongue recognition of traditional Chinese medicine(TCM).Methods A model of spotted tongue recognition and extraction is designed,which is based on the principle of image deep learning and instance segmentation.This model includes multiscale feature map generation,region proposal searching,and target region recognition.Firstly,deep convolution network is used to build multiscale low-and high-abstraction feature maps after which,target candidate box generation algorithm and selection strategy are used to select high-quality target candidate regions.Finally,classification network is used for classifying target regions and calculating target region pixels.As a result,the region segmentation of spotted tongue is obtained.Under non-standard illumination conditions,various tongue images were taken by mobile phones,and experiments were conducted.Results The spotted tongue recognition achieved an area under curve(AUC)of 92.40%,an accuracy of 84.30%with a sensitivity of 88.20%,a specificity of 94.19%,a recall of 88.20%,a regional pixel accuracy index pixel accuracy(PA)of 73.00%,a mean pixel accuracy(m PA)of73.00%,an intersection over union(Io U)of 60.00%,and a mean intersection over union(mIo U)of 56.00%.Conclusion The results of the study verify that the model is suitable for the application of the TCM tongue diagnosis system.Spotted tongue recognition via multiscale convolutional neural network(CNN)would help to improve spot classification and the accurate extraction of pixels of spot area as well as provide a practical method for intelligent tongue diagnosis of TCM.

Multi-level spherical moments based 3D model retrieval

In this paper a novel 3D model retrieval method that employs multi-level spherical moment analysis and relies on voxelization and spherical mapping of the 3D models is proposed. For a given polygon-soup 3D model, first a pose normalization step is done to align the model into a canonical coordinate frame so as to define the shape representation with respect to this orientation. Afterward we rasterize its exterior surface into cubical voxel grids, then a series of homocentric spheres with their center superposing the center of the voxel grids cut the voxel grids into several spherical images. Finally moments belonging to each sphere are computed and the moments of all spheres constitute the descriptor of the model. Experiments showed that Euclidean distance based on this kind of feature vector can distinguish different 3D models well and that the 3D model retrieval system based on this arithmetic yields satisfactory performance.

Analysis of Buddhist sculpture art in Wei, Jin, southern and Northern Dynasties

The emergence and development of Buddhist sculpture has completely changed the original Chinese ancient sculpture, rich China sculpture theme, greatly promote the development of the Chinese sculpture, in the Wei and Jin Dynasties, Buddhist sculpture received considerable development, the art form is abundant, representative of the ＂ slim but clear appearance＂ and＂ images of noble figures ＂two kinds of modeling features. From the perspective of historical background and aesthetic orientation, this paper analyzes and studies the overall features of the art of carving art in this historical period, as well as its profound influence on the development of Chinese Buddhist statues.

Combining Spectral with Texture Features into Objectoriented Classification in Mountainous Terrain Using Advanced Land Observing Satellite Image

Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.

“手”和上肢身体词组合研究

本文搜集了“手”和上肢身体词的双音组合16个,有三种结构:并列式4个,定中式11个,重叠式1个。其中定中式皆为“整体+部分”式。全面梳理这组词的用法,阐释词义,探明构词理据,描绘出词义引申轨迹,并归纳出9条常见的引申模式,进一步揭示其词义演变的规律及认知机制。其中相邻引申是最常见的词义引申模式。该组合的词义演变以“功能”“位置”为主要取象特征。