Radar micro-Doppler signatures are of great potential for identifying properties of unknown targets. An effective tool to extract information from the signatures is time-frequency analysis, based on which target ident...
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ISBN:
(纸本)0769522947
Radar micro-Doppler signatures are of great potential for identifying properties of unknown targets. An effective tool to extract information from the signatures is time-frequency analysis, based on which target identification and object recognition can be extended. In this paper, a method has been proposed for feature extraction and selection from simulated time-frequency distribution Of micro-Doppler dynamics. Experimental results have shown that a highly discriminative feature set can be established by using this method Withthis feature set, high classification performances both in training and testing stages for different classifiers have been achieved.
In this paper, an experimental comparison among three structural approaches to fingerprint classification is reported. Main pros and cons of such approaches are investigated by experiments and discussed. Moreover, the...
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In this paper we explore how a spectral technique suggested by quantum walks can be used to distinguish non-isomorphic cospectral graphs. Reviewing ideas from the field of quantum computing we recall the definition of...
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this paper shows how strings can be used in a natural images classification task. We propose to build an attributed string from a set of regions of interest detected thanks to an interest point detector. these salient...
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the RGB colour space is prominent as a colour representation and display scheme, although a number of other colour spaces have been developed over the years each with its own advantages and shortcomings with regard to...
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ISBN:
(纸本)3540263063
the RGB colour space is prominent as a colour representation and display scheme, although a number of other colour spaces have been developed over the years each with its own advantages and shortcomings with regard to its usefulness for colour/texture recognition. However, the recent advent of multiple classifier systems provides the unique opportunity to exploit the diverse information encapsulated in the different colour representations in a systematic fashion. In this paper we propose the use of classifier combination schemes which utilise information from different colour domains. We subsequently use suitable measures to investigate the diversity of the information infused by the different colour spaces. Experiments with two 40-class colour/texture datasets show the benefit of our multiple classifier approach, and reveal the existence of strong correlations between the accuracy achieved and the diversity measures. Finally, we illustrate, using quadratic regression, that there is significant scope to build and explore further (potentially causal) models of the observed relations between ensemble performance and diversity metrics. Our results point towards the use of diversity along with other statistical measures as possible predictors of the ensemble behaviour.
A typical recognition system consists of a sequential combination of two experts, called a detector and classifier respectively. the two stages are usually designed independently, but we show that this may be suboptim...
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In previous work, singular points (or top points) in the scale space representation of generic images have proven valuable for image matching. In this paper, we propose a construction that encodes the scale space desc...
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In this paper, we present a novel successive relaxation linear programming scheme for solving the important class of consistent labeling problems for which an L1 metric is involved. the unique feature of the proposed ...
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the proceedings contain 71 papers. the topics discussed include: soft computing algorithms applied to the segmentation of nerve cell images;patternrecognitionbased on time-frequency distributions of radar micro-Dopp...
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ISBN:
(纸本)0769522947
the proceedings contain 71 papers. the topics discussed include: soft computing algorithms applied to the segmentation of nerve cell images;patternrecognitionbased on time-frequency distributions of radar micro-Doppler dynamics;a quantitative software quality evaluation model for the artifacts of component based development;a new approach to software requirements elicitation;using data mining technology to design an intelligent CIM system for IC manufacturing;data mining for imprecise temporal associations;analysis of breast cancer using data mining and statistical techniques;analyzing the conditions of coupling existence based on program slicing and some abstract information-flow;a study of model layers and reflection;a general scalable implementation of fast matrix multiplication algorithms on distributed memory computers;error prediction for multi-classification;an integer support vector machine;and layered neural networks computations.
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