Magnetic and inductive sensors are widely used in research and industry for a variety of applications, e. g. for geophysical prospecting, non-destructive testing (NDT) of materials, in the food industries, for distanc...
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ISBN:
(纸本)9783642215377
Magnetic and inductive sensors are widely used in research and industry for a variety of applications, e. g. for geophysical prospecting, non-destructive testing (NDT) of materials, in the food industries, for distance and proximity sensing, security systems as well as for landmine detection. Metal detectors (MD), based on the eddy current principle, are the most used systems in humanitarian demining. Their main disadvantage is the high false alarm rate, caused by harmless metal objects and "uncooperative" soils with magnetic properties. The sensor signal (i.e. the induced complex coil voltage) is influenced by the object properties (material, shape). This paper describes an object recognition based on multi-parameter MD signals, which are classified by the fuzzy method. The ability to identify mines by their characteristic signature was demonstrated in test lanes for mine detection provided by the University of Rostock (Germany), JRC-Ispra (Italy) and the CTRO-Benkovac (Croatia).
Texture analysis is used in numerous applications in various fields. There have been many different approaches/techniques in the literature for texture analysis among which the texton-based approach that computes the ...
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ISBN:
(纸本)9783642215926;9783642215933
Texture analysis is used in numerous applications in various fields. There have been many different approaches/techniques in the literature for texture analysis among which the texton-based approach that computes the primitive elements representing textures using k-means algorithm has shown great success. Recently, dictionary learning and sparse coding has provided state-of-the-art results in various applications. With recent advances in computing the dictionary and sparse coefficients using fast algorithms, it is possible to use these techniques to learn the primitive elements and histogram of them to represent textures. In this paper, online learning is used as fast implementation of sparse coding for texture classification. The results show similar to or better performance than texton based approach on CUReT database despite of computation of dictionary without taking into account the class labels.
In this paper, we propose a new approach for detecting people in video sequences based on geometrical features and AdaBoost learning. Unlike its predecessors, our approach uses features calculated directly from silhou...
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ISBN:
(纸本)9783642215926;9783642215933
In this paper, we propose a new approach for detecting people in video sequences based on geometrical features and AdaBoost learning. Unlike its predecessors, our approach uses features calculated directly from silhouettes produced by change detection algorithms. Moreover, feature analysis is done part by part for each silhouette, making our approach efficiently applicable for partially-occluded pedestrians and groups of people detection. Experiments on real-world videos showed us the performance of the proposed approach for real-time pedestrian detection.
This paper presents an iterative Content Based Image Retrival(CBIR) system with Relevance Feedback (RF), in which M-band wavelet features are used as representation of images. The pixels are clustered using Fuzzy C-Me...
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ISBN:
(纸本)9783642217869
This paper presents an iterative Content Based Image Retrival(CBIR) system with Relevance Feedback (RF), in which M-band wavelet features are used as representation of images. The pixels are clustered using Fuzzy C-Means (FCM) clustering algorithm to obtain an image signature and Earth Mover's Distance (EMD) is used as a distance measure. Fuzzy entropy based feature evaluation mechanism is used for automatic computation of revised feature importance and similarity distance at the end of each iteration. The performance of the algorithm is tested on standard large multi-class image databases and compared with MPEG-7 visual features.
This article discusses a new document indexing scheme for information retrieval. For a structured (e.g., scientific) document, Pasi et al. proposed varying weights to different sections according to their importance i...
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ISBN:
(纸本)9783642217869
This article discusses a new document indexing scheme for information retrieval. For a structured (e.g., scientific) document, Pasi et al. proposed varying weights to different sections according to their importance in the document. This concept is extended here to unstructured documents. Each sentence in a document is initially assigned weight (significance in the document) with the help of a summarization technique. Accordingly, the term frequency of a term is decided as the sum of weights of the sentences the term belongs. The method is verified on a real life dataset using leading existing information retrieval models, and its performance has been found to be superior to conventional indexing schemes.
The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve th...
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ISBN:
(纸本)9781424441228
The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised patternrecognition techniques.
In this paper we present a new prediction technique to compress a pair of satellite images that have significant overlap in the underlying spatial areas. When this prediction technique is combined with an existing los...
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ISBN:
(纸本)9783642215957;9783642215964
In this paper we present a new prediction technique to compress a pair of satellite images that have significant overlap in the underlying spatial areas. When this prediction technique is combined with an existing lossless image set compression algorithm, the results are significantly better than those obtained by compressing each image individually. Even when there are significant differences between the two images due to factors such as seasonal and atmospheric variations, the new prediction technique still performs very well to achieve significant reduction in storage requirements.
A method for simultaneous non-Gaussian data clustering, feature selection and outliers rejection is proposed in this paper. The proposed approach is based on finite generalized Dirichlet mixture models learned within ...
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ISBN:
(纸本)9783642217869
A method for simultaneous non-Gaussian data clustering, feature selection and outliers rejection is proposed in this paper. The proposed approach is based on finite generalized Dirichlet mixture models learned within a framework including expectation-maximization updates for model parameters estimation and minimum message length criterion for model selection. Through a challenging application involving texture images discrimination, it is demonstrated that the developed procedure performs effectively in avoiding outliers and selecting relevant features.
The proceedings contain 39 papers. The topics discussed include: planar implementation of butler matrix feed network for a switched muitibeam antenna: a survey;comparative performance analysis of various training algo...
ISBN:
(纸本)9781467301329
The proceedings contain 39 papers. The topics discussed include: planar implementation of butler matrix feed network for a switched muitibeam antenna: a survey;comparative performance analysis of various training algorithms for control of CSTR process using NARMA-L2 control;a novel approach for face recognition and age estimation using local binary pattern, discriminative approach using two layered back propagation network;a comparative study of fuzzy classifiers on heart data;rough set analysis for uncertain data classification;shape, texture and local movement hand gesture features for Indian sign language recognition;efficient web service discovery model based on QOS and meta data instances;3D modeling of human faces- a survey;a novel image retrieval technique for enhanced telemedical applications;and a novel image retrieval technique for enhanced telemedical applications.
Ultrasonic techniques are wildly used in online partial discharge (PD) location and recognition for electrical transformers. This paper focuses on a new ultrasonic feature extraction method. The normalized discharge g...
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ISBN:
(纸本)9780769542966
Ultrasonic techniques are wildly used in online partial discharge (PD) location and recognition for electrical transformers. This paper focuses on a new ultrasonic feature extraction method. The normalized discharge grey moment features are extracted from ultrasonic signals to perform PD recognition. These features are sent to an improved BP neural network as to perform patternrecognition. Two types of PD patterns, pin-plate discharge and sphere-plate discharge, are tested, the PD patternrecognition method are compared with traditional methods and the recognition rates show that central grey moment has satisfactory ability in characterizing PD types, and the improved back propagation (BP) neural network perfectly met the recognition demands. Central grey moment provides us a novel approach to study partial discharge.
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