检索结果-内蒙古大学图书馆

IEEE Conference on Computer Vision and Pattern Recognition

作者： Haomiao Liu Ruiping Wang Shiguang Shan Xilin Chen Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS

ISBN: (纸本)9781467388528

In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large-scale datasets. While the complex image appearance variations still pose a great challenge to reliable retrieval, in light of the recent progress of Convolutional Neural Networks (CNNs) in learning robust image representation on various vision tasks, this paper proposes a novel Deep Supervised Hashing (DSH) method to learn compact similarity-preserving binary code for the huge body of image data. Specifically, we devise a CNN architecture that takes pairs of images (similar/dissimilar) as training inputs and encourages the output of each image to approximate discrete values (e.g. +1/-1). To this end, a loss function is elaborately designed to maximize the discriminability of the output space by encoding the supervised information from the input image pairs, and simultaneously imposing regularization on the real-valued outputs to approximate the desired discrete values. For image retrieval, new-coming query images can be easily encoded by propagating through the network and then quantizing the network outputs to binary codes representation. Extensive experiments on two large scale datasets CIFAR-10 and NUS-WIDE show the promising performance of our method compared with the state-of-the-arts.

关键词： image retrieval binary code hashing hashing method images discrete value image representation LOSS FUNCTION image data Propagating Imagery (Psychotherapy)

来源：评论

学校读者我要写书评

暂无评论

A Two-layer Cloud Database Model and Its Bidirectional Conversion Algorithms

A Two-layer Cloud Database Model and Its Bidirectional Conve...

引用

2016 IEEE 7th International Conference on Software Engineering and Service Science

作者： Ying Li Yuling Lu Guangxi Colleges and Universities Key Laboratory of Scientific Computing & Intelligent Information Processing Guangxi Teachers Education University

The existed cloud data models can not well meet the management requirements of structured data including a great deal of relational data,therefore a two-layer cloud data model consisting of a presentation layer and a storage layer is *** the presentation layer,the conception of composite class and composite object are defined to represent the structure and the data of structured data *** the storage layer,a composite class in the presentation layer is transformed into a3-tuple which preserves data structure in mappings between composite attributes and their sub-attributes by using a rule set;and a composite object in the presentation layer is transformed into another 3-tuple which preserves a structured data set in simple objects without embed objects by using a CAO(Component-Attribute-Object) set in which each element mainly consists of a simple object and the identification of its father *** order to store data in key-value model,a method to convert a CAO to a pair of key-value is ***,two algorithms were proposed to convert data between the representation layer and the storage *** experiment shows the two conversion algorithms are *** proposed model is fit for the management requirements of structured data in the cloud because composite object can represent structured data and avoid join operation of relation data and CAO can be stored in key-value model.

关键词： cloud database data model relational data keyvalue structured data

来源：评论

学校读者我要写书评

暂无评论

RGB-D Hand-Held Object Recognition Based on Heterogeneous Feature Fusion

引用

Journal of Computer Science & Technology 2015年第2期30卷 340-352页

作者：吕雄蒋树强 Luis Herranz 王双 Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Object recognition has many applications in human-machine interaction and multimedia retrieval. However, due to large intra-class variability and inter-class similarity, accurate recognition relying only on RGB data is still a big challenge. Recently, with the emergence of inexpensive RGB-D devices, this challenge can be better addressed by leveraging additional depth information. A very special yet important case of object recognition is hand-held object recognition, as manipulating objects with hands is common and intuitive in human-human and human-machine interactions. In this paper, we study this problem and introduce an effective framework to address it. This framework first detects and segments the hand-held object by exploiting skeleton information combined with depth information. In the object recognition stage, this work exploits heterogeneous features extracted from different modalities and fuses them to improve the recognition accuracy. In particular, we incorporate handcrafted and deep learned features and study several multi-step fusion variants. Experimental evaluations validate the effectiveness of the proposed method.

关键词： RGB-D hand-held object recognition heterogeneous features fusion

来源：评论

学校读者我要写书评

暂无评论

Tri-level combination for image representation 17th

Tri-level combination for image representation

引用

17th Pacific-Rim Conference on Multimedia, PCM 2016

作者： Li, Ruiying Zhang, Chunjie Huang, Qingming School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319488899

The context of objects can provide auxiliary discrimination beyond objects. However, this effective information has not been fully explored. In this paper, we propose Tri-level Combination for Image Representation (TriCoIR) to solve the problem at three different levels: object intrinsic, strongly-related context and weakly-related context. Object intrinsic excludes external disturbances and more focuses on the objects themselves. Strongly-related context is cropped from the input image with a more loose bound to contain surrounding context. Weaklyrelated one is recovered from the image other than object for global context. First, strongly and weakly-related context are constructed from input images. Second, we make cascade transformations for more intrinsical object information, which depends on the consistency between generated global context and input images in the regions other than object. Finally, a joint representation is acquired based on these three level features. The experiments on two benchmark datasets prove the effectiveness of TriCoIR. © Springer International Publishing AG 2016.

关键词： Image representation

来源：评论

学校读者我要写书评

暂无评论

Protein folding kinetic order prediction from amino acid sequence based on horizontal visibility network

引用

Current Bioinformatics 2016年第2期11卷 173-185页

作者： Zhao, Zhi-Qin Yu, Zu-Guo Anh, Vo Wu, Jing-Yang Han, Guo-Sheng Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University XiangtanHunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ4001 Australia School of Science Xi’an Shiyou University 18 Second Dianzi Road Yanta District Xi’anShaanxi710065 China

Protein folding is one of the most important problems in molecular biology. The kinetic order of protein folding is one of the main aspects of the folding process. Previous methods for predicting protein folding kinetic order require to use the information on tertiary or predicted secondary structure of a protein. In this paper, based on physicochemical properties of amino acids, we propose an approach to predict the protein folding kinetic order from the primary structure of a protein using support vector machine combined with principal component analysis. The horizontal visibility network, Hilbert-Huang transform, global descriptor, and Lempel-Ziv complexity are used to extract features in our approach. To evaluate our approach, the leave-one-out cross-validation test is employed on two widely-used data sets ("IvankovData" and "ZhengData" data sets) consisting of two-state and multi-state proteins. The overall accuracies of prediction can reach 83.87% for "IvankovData" data set and 85% for "ZhengData" data set respectively. Comparisons with the existing methods show that the present approach performs better on the "IvankovData" data set. These results indicate that the present approach is effective and valuable for predicting protein folding kinetic order. Based on factor analysis, we find that the length of protein sequence, hydrophobicity and hydrophilicity of amino acids are important features in our approach. © 2016 Bentham Science Publishers

关键词： Hilbert-Huang transform

来源：评论

学校读者我要写书评

暂无评论

Color holographic zoom system based on a liquid lens

引用

Chinese Optics Letters 2015年第7期13卷 96-100页

作者：王迪王琼华沈川周昕刘超 School of Electronics and Information Engineering Sichuan University Key Laboratory of Intelligent Computing and Signal Processing Ministry of EducationAnhui University

In this Letter, we propose a color holographic zoom system based on a liquid lens. We use the spatial multiplexing method to realize color reconstruction. By controlling the focal lengths of the liquid lens and the encoded digital lens on the spatial light modulator panel, we can change the magnification of the reconstructed image very quickly, without mechanical parts and keeping the output plane stationary.

关键词： Color Holography Light modulators Multiplexing

来源：评论

学校读者我要写书评

暂无评论

An integratable verifiable secret sharing mechanism

引用

International Journal of Network Security 2016年第4期18卷 617-624页

作者： Liu, Yanjun Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No. 111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No. 500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No. 100 Wenhwa Rd Seatwen Taichung413 Taiwan

Threshold secret sharing (SS), also denoted as (t, n) SS, has been used extensively in the area of information se- curity, such as for group authentication, cloud storage schemes, secure parallel communication and wireless mul- tipath routing protocols. However, a (t, n) SS cannot de- tect any deceptions among the dealer and shareholders. Veriable secret sharing (VSS) overcomes the weakness of (t, n) SS in such a way that it is able to detect cheaters by verifying the validity of shares or the correctness of the recovered secret under the condition that both shares and the secret are not compromised. Recently, two non- interactive VSSs based on Asmuth-Bloom's SS were pro- posed by Harn et al. and Liu et al., respectively. Both VSSs require shareholders to examine the range of values of some integers related to the secret before recovering the secret, which is a time-consuming operation. In this paper, we propose a novel integratable VSS mechanism that integrates the concepts of the generalized Chinese remainder theorem (GCRT), Shamir's SS and Asmuth- Bloom's SS. Our proposed VSS can verify that the secret reconstructed by any t or more shareholders is the same as the one that the dealer has generated. Analysis shows that our proposed VSS can provide perfect secrecy and better efficiency.

关键词： Hash functions

来源：评论

学校读者我要写书评

暂无评论

A System for Diagnosis of Wheat Leaf Diseases Based on Android Smartphone

A System for Diagnosis of Wheat Leaf Diseases Based on Andro...

引用

International Symposium on Optoelectronic Technology and Application 2016(OTA 2016)——Conf.13 Environmental Monitoring and Safety Testing Technology

作者： Xinhua Xie Dong Liang Dongyan Zhang Linsheng Huang Xiangqian Zhang Key Laboratory of Intelligent Computing & Signal processing Ministry of EducationAnhui University School of Electronic and Information Engineering of Anhui University

Owing to the shortages of inconvenience, expensive and high professional requirements etc. for conventional recognition devices of wheat leaf diseases, it does not satisfy the requirements of uploadin

关键词：

来源：评论

学校读者我要写书评

暂无评论

Kernelized Cross-Modal Hashing for Multimedia Retrieval

Kernelized Cross-Modal Hashing for Multimedia Retrieval

引用

World Congress on intelligent Control and Automation

作者： Shoubiao Tan Lingyu Hu Anqi Wang-Xu Jun Tang Zhaohong Jia Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University School of Electronics and Information Engineering Anhui University

ISBN: (纸本)9781467384155

Cross-modal hashing has received more and more attention because of its fast query speed and low storage cost. In this paper, we propose a flexible yet simple cross-modal hashing method to deal with the problem of cross-modal retrieval. The proposed method consists of two steps. In the first phase, we use a kernel canonical correlation analysis method named Anchor kernel canonical correlation analysis (AKCCA) to map data from different modalities into a common kernel space. In the second phase, we use the method named Supervised Hashing with Kernels (KSH) to learn hashing functions bit by bit. These two useful ingredients are combined seamlessly to achieve promising results. Experimental results on a benchmark dataset demonstrate that our method performs better than several state-of-the-art methods.

关键词： Cross-modal hashing Seeds second phase multivariate analysis Kernel

来源：评论

学校读者我要写书评

暂无评论

To Obtain the OWA Weighting Vector Via Normal Distribution Function

To Obtain the OWA Weighting Vector Via Normal Distribution F...

引用

2015 International Conference on Social Science,Education Management and Sports Education(SSEMSE 2015)

作者： Zhiwei LI Xiyang YANG School of Mathematics and Computer Science Quanzhou Normal University Key Laboratory of Intelligent Computing and Information Processing Fujian Province University

The OWA operator is an important assessment method in multiple-attribute decision making. A new model based on the density function of normal distribution is given to assign reasonable weights of OWA operators. Using the orness level as a parameter in this method, one can deduce OWA weights by solving a quadratic programing problem. Three propositions of this new model are proven, and a numerical example about the assessment of red wines is given to analyze and illustrate this method.

关键词： OWA operators normal distribution weighting vector

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：