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A spatial attentive and temporal dilated(SATD)GCN for skeleton-based action recognition

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CAAI Transactions on Intelligence Technology 2022年第1期7卷 46-55页

作者： Jiaxu Zhang Gaoxiang Ye Zhigang Tu Yongtao Qin Qianqing Qin Jinlu Zhang Jun Liu State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina State Grid Wuhan Power Supply Company WuhanChina Shenzhen Infinova Ltd.Company ShenzhenChina Information Systems Technology and Design Pillar Singapore University of Technology and DesignSingapore

Current studies have shown that the spatial-temporal graph convolutional network(STGCN)is effective for skeleton-based action recognition.However,for the existing STGCN-based methods,their temporal kernel size is usually fixed over all layers,which makes them cannot fully exploit the temporal dependency between discontinuous frames and different sequence lengths.Besides,most of these methods use average pooling to obtain global graph feature from vertex features,resulting in losing much fine-grained information for action classification.To address these issues,in this work,the authors propose a novel spatial attentive and temporal dilated graph convolutional network(SATD-GCN).It contains two important components,that is,a spatial attention pooling module(SAP)and a temporal dilated graph convolution module(TDGC).Specifically,the SAP module can select the human body joints which are beneficial for action recognition by a self-attention mechanism and alleviates the influence of data redundancy and noise.The TDGC module can effectively extract the temporal features at different time scales,which is useful to improve the temporal perception field and enhance the robustness of the model to different motion speed and sequence length.Importantly,both the SAP module and the TDGC module can be easily integrated into the ST-GCN-based models,and significantly improve their performance.Extensive experiments on two large-scale benchmark datasets,that is,NTU-RGB+D and Kinetics-Skeleton,demonstrate that the authors’method achieves the state-of-the-art performance for skeleton-based action recognition.

关键词： classification. skeleton action

Multi-label dimensionality reduction and classification.with extreme learning machines

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Journal of Systems Engineering and Electronics 2014年第3期25卷 502-513页

作者： Lin Feng Jing Wang Shenglan Liu Yao Xiao Faculty of Electronic Information and Electrical Engineering School of Computer Science and TechnologyDalian University of Technology School of Innovation Experiment Dalian University of Technology

In the need of some real applications, such as text categorization and image classification. the multi-label learning gradually becomes a hot research point in recent years. Much attention has been paid to the research of multi-label classification.algorithms. Considering the fact that the high dimensionality of the multi-label datasets may cause the curse of dimensionality and wil hamper the classification.process, a dimensionality reduction algorithm, named multi-label kernel discriminant analysis （MLKDA）, is proposed to reduce the dimensionality of multi-label datasets. MLKDA, with the kernel trick, processes the multi-label integrally and realizes the nonlinear dimensionality reduction with the idea similar with linear discriminant analysis （LDA）. In the classification.process of multi-label data, the extreme learning machine （ELM） is an efficient algorithm in the premise of good accuracy. MLKDA, combined with ELM, shows a good performance in multi-label learning experiments with several datasets. The experiments on both static data and data stream show that MLKDA outperforms multi-label dimensionality reduction via dependence maximization （MDDM） and multi-label linear discriminant analysis （MLDA） in cases of balanced datasets and stronger correlation between tags, and ELM is also a good choice for multi-label classification.

关键词： multi-label dimensionality reduction kernel trick classification.

A Study on the classification.and Well-Logging Identification of Eclogite in the Main Hole of Chinese Continental Scientific Drilling Project

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Journal of China University of Geosciences 2007年第4期18卷 357-365页

作者：景建恩魏文博金胜叶高峰邓明 Key Laboratory of Geo-detection (China University of Geosciences Beijing)Ministry of Education State Key Laboratory of Geological Processes and Mineral Resources China University of Geosciences School of Geophysics and Information Technology China University of Geosciences

Eclogite, one of the important lithologies in the main hole of the Chinese Continental Scientific Drilling （CCSD） Project, exists above the depth of 3 245 m and has distinctive responses of gamma-ray, compensating density and neutron well-logging, and so on. In this study, according to the diversities of minerals and chemical components and well-logging responses, edogites are classified from three aspects of origin, content of oxygen, and sub-mineral. We studied the logging identification method for eclogite sub-classes based on multi-element statistics and reconstructed 11 kinds of eclogite. As a result, eclogites can be divided into 6 types using well logs. In the light of this recognition, the eclogite in the main hole is divided into 20 sections, and the distribution characters of all sub-classes of eclogite are analyzed, which will provide important data for geological research of CCSD.

关键词： Chinese Continental Scientific Drilling （CCSD） ultrahigh pressure metamorphic rock eclogite well-logging lithology identification classification.

Editorial comment on:“Systemic treatment of hepatocellular carcinoma:an EASL position paper”

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Hepatobiliary Surgery and Nutrition 2022年第1期11卷 112-114页

作者： Daniel H.Ahn Tanios Bekaii-Saab Division of Hematology/Medical Oncology Mayo Clinic ArizonaPhoenixAZUSA

Hepatocellular carcinoma is the most common cancer of the liver and worldwide,the sixth most common cancer and the third most common cause of cancer related deaths(1).The management and treatment of this disease requires a multi-disciplinary approach,which is observed in the staging and classification.In 1999,the development of the Barcelona Clinic Liver Cancer(BCLC)classification.system helped to guide the appropriate treatments based on stage.While patients with stage A disease would be candidates for locoregional treatment including surgical resection,liver transplantation or liver directed therapy,treatment in patients with intermediate(B)or advanced(C)stage disease would be palliative,where the recommendation would for systemic therapy.

关键词： classification. treatment cancer

Decision tree support vector machine based on genetic algorithm for multi-class classification

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Journal of Systems Engineering and Electronics 2011年第2期22卷 322-326页

作者： Huanhuan Chen Qiang Wang Yi Shen School of Astronautics Harbin Institute of Technology Harbin 150001 P. R. China

To solve the multi-class fault diagnosis tasks, decision tree support vector machine （DTSVM）, which combines SVM and decision tree using the concept of dichotomy, is proposed. Since the classification.performance of DTSVM highly depends on its structure, to cluster the multi-classes with maximum distance between the clustering centers of the two sub-classes, genetic algorithm is introduced into the formation of decision tree, so that the most separable classes would be separated at each node of decisions tree. Numerical simulations conducted on three datasets compared with ＂one-against-all＂ and ＂one-against-one＂ demonstrate the proposed method has better performance and higher generalization ability than the two conventional methods.

关键词： support vector machine （SVM） decision tree geneticalgorithm classification.

Remote sensing data classification.using tolerant rough set and neural networks

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Science China Earth Sciences 2005年第12期48卷 2251-2259页

作者： MA Jianwen HASI Bagan State Key Laboratory of Remote Sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China State Key Laboratory of Remote Sensing Science Institute of Remote Sensing Applications Chinese Academy of Sciences Beijing 100101 China

BP algorithm of neural net is used more in remote sensing data classification. One of drawbacks of BP algorithm is the overall low function when the net is training. To avoid this kind of problem, the paper introduces the tolerant rough set for classification.preprocessing the training data to reduce the influence elements of the training convergence in order to improve the net training successful rate. ETM+ data of Beijing in May 2003 is selected in the study. ETM+ data before and after classification.preprocessing, respectively, are used for BP (Back propaga-tion) training. The result shows that such a preprocessing not only compensates the drawback of BP algorithm when processing ETM+ data but also improves classification.accuracy.

关键词： tolerant rough set, neural network, BP algorithm, classification.

Identification and classification.of subspecies of Asian cultivated rice and their hybrids

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Chinese Science Bulletin 1998年第22期43卷 1864-1872页

作者： Xiangkun Wang Renhua Li Chuanqing Sun Zichao Li Hongwei Cai Xinli Sun China Agr Univ Beijing 100094 Peoples R China

Having reviewed the major classification.systems proposed by various scholars across the world, it is found that \%indica\% and \%japonica\% under \%O.sativa\% L. are two major directions thoroughly differentiated from the Asian cultivated rice, forming the framework of the classification.structure. A system with \%indica\% and \%japonica\% as the only two subspecies is therefore reiterated.There are various ways to determine the indica_japonica identity of hybrid rice, but the "combined morphological trait index"(CMT index) method is more efficient and easier to handle, although the isozyme analysis, molecular marker analysis and grain quality assay methods are also feasible.

关键词： Asian cultivated rice subspecies intersubspecific hybrids identification classification.

Multi-criteria classification.approach with polynomial aggregation function and incomplete certain information

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Journal of Systems Engineering and Electronics 2006年第3期17卷 546-550页

作者： Wang Jianqiang School of Business Central South Univ. Changsha 410083 P. R. China

The relationship between the importance of criterion and the criterion aggregation function is discussed, criterion＇s weight and combinational weights between some criteria are defined, and a multi-criteria classification.method with incomplete certain information and polynomial aggregation function is proposed. First, linear programming is constructed by classification.to reference alternative set （assignment examples） and incomplete certain information on criterion＇s weights. Then the coefficient of the polynomial aggregation function and thresholds of categories are gained by solving the linear programming. And the consistency index of alternatives is obtained, the classification.of the alternatives is achieved. The certain criteria＇s values of categories and uncertain criteria＇s values of categories are discussed in the method. Finally, an example shows the feasibility and availability of this method.

关键词： multi-criteria decision-making incomplete certain information polynomial function classification.

Consistency argument and classification.problem in λ-calculus

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Science China(Technological Sciences) 1999年第5期42卷 502-506页

作者：王驹赵希顺黄且圆蒋颖 Institute of Software Chinese Academy of Sciences

Enlightened by Mal’cev theorem in universal algebra, a new criterion for consistency argument in λ-calculus has been introduced. It is equivalent to Jacopini and Baeten-Boerboom’ s, but more convenient to use. Based on the new criterion, one uses an enhanced technique to show a few results which provides a deeper insight in the classification.problem of λ-terms with no normal forms.

关键词： λ-term consistency classification.