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The evidence reasoning is one method to reason uncertainty of artificial intelligence and has better performance of decision ability under the uncertainty situation. In this paper, the evidence reasoning is introduced to distributed decision system. The method is presented to distributed intelligent decision based on the transferable belief model. The agent model and distributed decision system architecture...
With the aim to share and reuse conceptual design process knowledge, the paper proposed to apply one knowledge discovery approach-DFSSM in product conceptual design. According to the feature of conceptual design, one new approach of product conceptual design based on DFSSM was implemented, in which the DFSSM could mine design process knowledge from complex type data of conceptual design and the knowledge...
The research proposes an approach of story segmentation for news video using multimodal analysis. The approach detects the topic-caption frames, and integrates them with silence clips detection, as well as shot segmentation to locate news story boundaries. On test data with 135,400 frames, the accuracy rate 87.9% and the recall rate 98.7% are obtained. The experimental results show the approach is...
Semantic soccer video analysis has attracted more and more attention recently. In this paper, we present a football event detection method by using multiple feature extraction and fusion. Instead of using low-level features, the proposed method is built upon visual, auditory features, text and audio keywords. Promising event detection results have been achieved. By using the proposed method, we have...
Classification is a famous branch of machine learning. We have tried many ways to invent and improve algorithms to get better results from given data. However, few have been done on how to revise data to adapt machine learning. In this paper, the same classifiers are implemented on same object sets which are different in the granularity of classification to show different classification can make great...
Based on wavelet and principal component analysis(PCA), an effective shell texture feature of the coscinodiscus extraction method for classification is proposed in this paper.The feature extraction process involves a normalization of the given image with different sizes followed by shift invariant wavelet transform. The shift invariant feature is computed for subband of wavelet coefficients by PCA...
In this paper, we propose a real-time forest fire detection algorithm using artificial neural networks based on dynamic characteristics of fire regions segmented from video images. Fire region is obtained from image with the help of threshold values in HSV color space. Area, roundness and contour are computed for fire regions from each 5 continuous frames. The average and mean square deviation of...
Neural network is a technology for intelligent transportation system and it is important in vehicle type recognition. However, traditional vehicle type recognition method always utilize BP network. A new vehicle type recognition based on radial basic function neural network was proposed. Also discussed are the problem of feature of vehicle feature vector, the problem of normalization of the image-size,...
Vehicle type recognition is an active subject in the area of computer pattern recognition, which has been a focus in reach for the last couple of decades because of its wide potential application. And edge detection is an important step for vehicle type recognition, a vehicle type recognition method based on Sobel was proposed. Also discussed are the vehicle vector and the vehicle recognize process...
Vehicle type automatic recognition is of great important today in intelligent transportation system. And neural network is often applied to recognize the vehicle type. However, the network can be very complex and therefore difficult to be trained. In order to cope with such issues, a new developed vehicle type recognition method based on contour feature is presented in this study. It is applied to...
In this paper, an algorithm using point feature and intensity feature combined with the Artificial Immune algorithm is presented. First, the feature points of the two images are extracted by Harris corner detector to reduce the amount of computation. Then, the mutual information (MI) is used to be the similarity measure for MI algorithm based on intensity has excellent robustness and accuracy. Finally,...
This paper deals with the problem of recognizing textures in images. For this purpose we employ a technique based on the fractal dimension (FD) and a new fractal dimension estimating method is proposed by taking the area instead of the volume covering in box-counting to estimate the FD. Three FD features are based on the original image, the above average/high gray level image, the below average/low...
The advance of image capture device and the popularity of the Internet have made the World Wide Web the biggest and most diverse repository of images. How to retrieve images fast and accurately from the WWW has become an urgent problem to be solved. Although many commercial Web image search engine has come forth, the precision is not satisfying for the reason that the text in the pages which they...
Duplicated web pages responded by search engines not only waste valuable storage, but also aggravate burdens of userspsila browse. Web page de-duplication can effectively improve the information retrieval. This paper proposes pretreatment of web pages to improve the effectiveness and efficiency of web page de-duplication based on feature code according to the principle of data clearing. This paper...
In this paper, we propose a novel framework of large-scale and real-time image annotation system. The large-scale image set is constructed based on current Web image search engines and re-ranking algorithm. Various global and local features are employed for representing images with parallel extraction mechanism for the real-time requirements. At training stage, the distance between class centers in...
In intrusion detection data set is high dimensional, which leads to low processing speed for intrusion detection algorithms, but it holds many features affecting little for detection. To address the above issue, a two-step feature selection algorithm is proposed in this paper. Depending on the definition of relevant feature and redundant feature and using mutual information as criterion, it firstly...
A novel framework referred to as visual vocabulary labeling is proposed for 3D object retrieval. It aims at localizing the visual semantics to 3d object with textual modalities. Two main processes are included in the presented framework. One is automatic labeling from 3D object to visual vocabulary. The other is visual vocabulary based retrieval with relevance feedback. The probabilistic model and...
Partial discharge (PD) gray intensity image is regarded as the research object in this paper, a new principle and method based on genetic programming is proposed to extract PD features aiming at PRPD mode, This article firstly introduces the PRPD mode and the method to get the three-dimensional spectrum and two-dimensional gray intensity image, then gray intensity images identification technology...
We propose a novel way to apply independent component analysis (ICA) on eight kinds of visual descriptors (features), and combine the eight features of the same database to extract independent component (IC) feature of each feature. A comparative study on the retrieval performance has been done between the original features and IC features in four image databases. Experiment results show that the...
An elaborately designed software architecture is put forward based on fuzzy sets theory (FST), which is specialized in multiple sensor fusion and mechanism failure diagnosis. Besides, when confronted with multiple fault signals, fusion parameters can be dynamically adapted based on principles of fuzzy soft clustering so as to promote immune ability in artificially mechanical systems. The key point...
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