In this paper, we describe a novel method to create the complete 3D model of the object on uncalibrated images. First, we match the points both detected by multi-scale Harris corner detection algorithm and line detect...
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We investigate further our intelligent machine vision system for patternrecognition and texture image classification. A database of about 335 texture images of industrial cork tiles is used for this research. The ima...
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ISBN:
(纸本)9780889868632
We investigate further our intelligent machine vision system for patternrecognition and texture image classification. A database of about 335 texture images of industrial cork tiles is used for this research. The images need to be classified into several classes based on their texture features similarities. In this work, we assume that there is no a priori human vision expert knowledge about the classes. After pre-processing of the data, feature extraction and conducting statistical analysis by applying principal component analysis (PCA) and linear discriminant analysis (LDA), we investigate unsupervised neural network learning. Self-organizing map (SOM) neural networks are trained, tested and validated and the obtained results are discussed and critically compared with research works investigating similar approaches.
This publication presents the use of semantic data analysis in cognitive processes of data analysis, interpretation, recognition and understanding in advanced pattern understanding systems. These processes form a part...
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Classification of evolving data stream requires adaptation during exploitation of algorithms to follow the changes in data. One of the approaches to provide the classifier the ability to adapt changes is usage of slid...
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ISBN:
(纸本)9783642238567
Classification of evolving data stream requires adaptation during exploitation of algorithms to follow the changes in data. One of the approaches to provide the classifier the ability to adapt changes is usage of sliding window - learning on the basis of the newest data samples. Active learning is the paradigm in which algorithm decides on its own which data will be used as training samples;labels of only these samples need to be obtained and delivered as the learning material. This paper will investigate the error of classic sliding window algorithm and its active version, as well as its learning curve after sudden drift occurs. Two novel performance measures will be introduces and some of their features will be highlighted.
Due to improve the rate of accuracy of face detection when illuminating condition, face position, face expression was changeable, proposed LTP (local ternary patterns) features of image which is a generalization of th...
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Recent pandemics such as Swine Flu, have caused concern for public health officials. Given the ever increasing pace at which infectious diseases can spread globally, officials must be prepared to react sooner and with...
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In plant development biology, the study of the structure of the plant's root is fundamental for the understanding of the regulation and interrelationships of cell division and cellular differentiation. This is bas...
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ISBN:
(纸本)9783642215957;9783642215964
In plant development biology, the study of the structure of the plant's root is fundamental for the understanding of the regulation and interrelationships of cell division and cellular differentiation. This is based on the high connection between cell length and progression of cell differentiation and the nuclear state. However, the need to analyse a large amount of images from many replicate roots to obtain reliable measurements motivates the development of automatic tools for root structure analysis. We present a novel automatic approach to detect cell files, the main structure in plant roots, and extract the length of the cells in those files. This approach is based on the detection of local cell file characteristic symmetry using a wavelet based image symmetry measure. The resulting detection enables the automatic extraction of important data on the plant development stage and of characteristics for individual cells. Furthermore, the approach presented reduces in more than 90% the time required for the analysis of each root, improving the work of the biologist and allowing the increase of the amount of data to be analysed for each experimental condition. While our approach is fully automatic a user verification and editing stage is provided so that any existing errors may be corrected. Given five test images it was observed that user did not correct more than 20% of all automatically detected structure, while taking no more than 10% of manual analysis time to do so.
Rough Set theory represents a promising technique to handle imperfect knowledge, which has found interesting extensions and various applications. This paper presents a note on rough set theory that will be useful for ...
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Rough Set theory represents a promising technique to handle imperfect knowledge, which has found interesting extensions and various applications. This paper presents a note on rough set theory that will be useful for beginners.
Proceedings oftheSixthinternationalconference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesnt on...
ISBN:
(数字)9783642256615
ISBN:
(纸本)9783642256608
Proceedings oftheSixthinternationalconference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesnt only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, patternrecognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Yinglin Wang is a professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China; Dr. Tianrui Li is a professor at the School of Information Science and Technology, Southwest Jiaotong University, China.
This paper proposes a new fault diagnosis methodology for of high power factor rectifiers. This method Is based on the combined with input line currents three dimensional space and the use of the on Principal Componen...
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