图像数据库的保局聚类

面对日益增长的图像数据库,为用户提供一个简洁高效的搜索和浏览解决方案成为一个紧迫而且充满挑战的问题．图像聚类技术可以在许多方面为此提供帮助,例如图像数据预处理、用户界面设计．以及对搜索结果的聚类等．在众多聚类算法中,谱聚类（spectral clustering）方法由于能够解决复杂分布数据的聚类问题,以及接近全局最优的性能,成为近年来广受关注的一种方法．然而,目前存在的谱聚类方法,譬如normalized cut在处理新增数据点的聚类时,计算复杂度很高．提出了一种新的聚类算法——保局聚类．保局聚类在拥有许多非线性谱聚类方法优点的同时,又具有独特的数学特性——能提供显式的映射函数．这为在原数据集和新增数据集上进行高效的聚类提供了可能．实验结果显示,保局聚类比K均值聚类和主成分分析后的K均值聚类效果要好．实验同样显示,保局聚类与normalized cut效果可比,而前者更加高效．     

Facial expression recognition based on two-dimensional discriminant locality preserving projections

In this paper, a novel method called two-dimensional discriminant locality preserving projections (2D-DLPP) is proposed. By introducing between-class scatter constraint and label information into two-dimensional locality preserving projections (2D-LPP) algorithm, 2D-DLPP successfully finds the subspace which can best discriminate different pattern classes. So the subspace obtained by 2D-DLPP has more discriminant power than 2D-LPP, and is more suitable for recognition tasks. The proposed method was applied to facial expression recognition tasks on JAFFE and Cohn-Kanade database and compared with other three widely used two-dimensional methods: 2D-PCA, 2D-LDA and 2D-LPP. The high recognition rates show the effectiveness of the proposed algorithm.     

基于 PTM潜在 DirichIet 分配的少量标记样本文本分类

针对现实文本分类环境下通常仅有少量标记样本而影响分类精度的问题,提出了一种基于概率主题模型潜在 Dirichlet 分配的分类算法。借助标准词频逆文档频率函数将每个文档表示成术语权重向量;利用概率主题模型预处理以简化文档,并从文档中提取术语;再利用潜在 Dirichlet 分配模型进行关系学习,构建基于图的分类器完成分类。在公开的 Reuters-21578资源库上的分类实验评估了该方法的有效性,相比分类效果较好的支持向量机,该方法在大部分情况下能够取得更高的分类精度。     

基于局部相似性的视频镜头分割*

为了进一步提高视频镜头的分割精度,提出了一种基于局部相似性的视频镜头分割方法。首先为了有效地进行视频特征降维,提出了改进的保局投影算法,利用仿射传播聚类算法得到具有相同模式的相似样本,根据相似样本构建连接矩阵,并根据降维前后模式的相关系数确定最佳降维维数,该算法有效地保留了数据的局部分布信息;然后利用具有相同模式的相似样本构建局部支持向量机检测镜头边界。实验结果表明,该方法利用样本的局部相似性特点,在视频特征提取和镜头边界检测两个阶段提高了镜头分割精度。     

Regularized locality preserving discriminant analysis for face recognition

This paper proposes a regularized locality preserving discriminant analysis (RLPDA) approach for facial feature extraction and recognition. The RLPDA approach decomposes the eigenspace of the locality preserving within-class scatter matrix into three subspaces, i.e., the face space, the noise space and the null space, and then regularizes the three subspaces differently according to their predicted eigenvalues. As a result, the proposed approach integrates discriminative information in all of the three subspaces, de-emphasizes the effect of the eigenvectors corresponding to the small eigenvalues, and meanwhile suppresses the small sample size problem. Extensive experiments on ORL face database, FERET face subset and UMIST face database illustrate the effectiveness of the proposed approach.     

多损失融合的小样本光伏组件隐裂检测算法

针对工业生产线光伏组件隐性纹检测问题,为了降低人力成本,提高检测效率,并快速适应新型产品的隐裂检测,提出了一种多损失融合的小样本光伏组件隐裂检测算法.首先,为丰富卷积神经网络提取的语义信息,引入了Transformer的多头注意力机制,缓解各批次产品的分布差异对隐裂检测的影响,促使模型从多样化产品中关注于隐裂信息;其次...     

3Desque: interface elements for a 3D graphical user interface

This paper explores some design possibilities and constraints for 3D enhancements of graphical user interfaces (GUIs). This is done with the aim of conveying more information in less screen space, while avoiding visual clutter. Design elements include the use of ‘slapped‐back’ windows obtained by projecting windows and icons into three dimensions; ‘trays’, an alternative to folders or piles; the use of transparent ‘beams’ for indicating hierarchy; and the use of ‘periphs’ for a form of fisheye projection on window borders. In addition we employ shading and shadows to enhance the interface, and automatic placement algorithms to prevent visually confusing occlusion. By considering these approaches together, rather than in isolation, the interactions between the different modifications are made explicit. Copyright © 1999 John Wiley & Sons, Ltd.