Quality abnormal patternrecognition for dynamic process is the key problem to achieve the online quality control and diagnose of automatic production. In the practical applications, there are some existing problems s...
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ISBN:
(纸本)9783037859728
Quality abnormal patternrecognition for dynamic process is the key problem to achieve the online quality control and diagnose of automatic production. In the practical applications, there are some existing problems such as computational complexity and low recognition accuracy. A recognition method for quality abnormal pattern of dynamic process with PCA-SVM was proposed. This paper proposes a feature selection technique that employs a principal component analysis, to avoid this information loss. Then, the extracted features were treated as input vector for SVM classifier, following a particle swarm optimization algorithm is proposed to improve the generalization performance of the recognizer. Simulation results show that the proposed algorithm has very high recognition accuracy and high generalization ability. It is significant for quality monitoring and diagnosis in manufacture dynamic process.
Pairwise dissimilarity representations are frequently used as an alternative to feature vectors in patternrecognition. One of the problems encountered in the analysis of such data, is that the dissimilarities are rar...
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ISBN:
(纸本)9783319023090
Pairwise dissimilarity representations are frequently used as an alternative to feature vectors in patternrecognition. One of the problems encountered in the analysis of such data, is that the dissimilarities are rarely Euclidean, while statistical learning algorithms often rely on Euclidean distances. Such non-Euclidean dissimilarities are often corrected or imposed geometry via embedding. This talk reviews and and extends the field of analysing non-Euclidean dissimilarity data.
In this paper a novel approach for reliable detection and accurate localization of X-corner fiducial markers is presented, which is particularly designed for Image Guided Surgery (IGS). The key idea is to combine two ...
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In this paper, a fully automatic method is proposed for the detection of prostate cancer within the peripheral zone. The method starts by filtering noise in the original image followed by feature extraction and smooth...
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The recent technological progress contributes to a huge increase of 3D models available in digital forms. Numerous applications were developed to deal with this amount of information, especially for 3D shape retrieval...
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The proceedings contain 25 papers. The topics discussed include: cloud and mobile security: challenges and future research directions;DLP-technologies: new directions and trends;using fuzzy logic to evaluate trust in ...
The proceedings contain 25 papers. The topics discussed include: cloud and mobile security: challenges and future research directions;DLP-technologies: new directions and trends;using fuzzy logic to evaluate trust in e-commerce;gamification of teaching and learning activity: prospect and challenges of mobile game-based learning;ComboSplit: combining various splitting criteria for building a single decision tree;text classification using computational model of the cerebral cortex;restricted Boltzmann machines for modeling businesses;variables selection for multiclass SVM using the multiclass radius margin bound;on the enumeration of frequent patterns in sequences;predicting movie incomes using search engine query data;best-parameterized sigmoid ELM for benign and malignant breast cancer detection;inference engine for classification of expert systems using keyword extraction technique;comparison of classifiers for retinal pathology images using surf and bag-of-words model;content based video quality control for wide-area video surveillance systems;line detection by centre and width estimation;and interactive versus passive 2D face spoofing detection.
In this paper, we intend to introduce a fast surface registration process which is independent from the original parameterization of the surface and invariant under 3D rigid transformations. It is based on a feature d...
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Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones. While many subsequences have improved the work with more powerful learning algorithms, the feature representation us...
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ISBN:
(纸本)9781479935840
Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones. While many subsequences have improved the work with more powerful learning algorithms, the feature representation used for face detection still can't meet the demand for effectively and efficiently handling faces with large appearance variance in the wild. To solve this bottleneck, we borrow the concept of channel features to the face detection domain, which extends the image channel to diverse types like gradient magnitude and oriented gradient histograms and therefore encodes rich information in a simple form. We adopt a novel variant called aggregate channel features, make a full exploration of feature design, and discover a multi-scale version of features with better performance. To deal with poses of faces in the wild, we propose a multi-view detection approach featuring score re-ranking and detection adjustment. Following the learning pipelines in Viola-Jones framework, the multi-view face detector using aggregate channel features shows competitive performance against state-of-the-art algorithms on AFW and FDDB testsets, while runs at 42 FPS on VGA images.
It is presented the design and construction of a pieces system classifier through visual control, in which six characteristics of the image are extracted and the four of major discriminative are selected. As a classif...
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This paper proposes a patternrecognition approach based on the back propagation (BP) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). pattern...
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ISBN:
(纸本)9783038351559
This paper proposes a patternrecognition approach based on the back propagation (BP) neural network for identifying insulation defects of high-voltage electrical apparatus arising from partial discharge (PD). patternrecognition of PD is used for identifying defects causing the PD, such as internal discharge, external discharge, corona, etc. This information is vital for estimating the harmfulness of the discharge in the insulation. Since an insulation defect, such as one resulting from PD, would have a corresponding particular pattern, patternrecognition of PD is significant means to discriminate insulation conditions of high-voltage electrical apparatus. To verify the proposed approach, experiments were conducted to demonstrate the field-test PD patternrecognition of model insulators with artificial defects are purposely created to produce the common PD activities of insulators by using feature vectors of field-test PD patterns. The experimental data are found to be in close agreement with the recognized data. The experimental results show that the proposed approach is very effective for recognizing the defects of high-voltage electrical apparatus.
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