the productivity of a fabrication is determined by the weakest member. there are many test benches in the ceramic industry today, with inspectors, who qualify the manufactured products according to subjective points o...
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the ARCADIA project aims at developing automatic image analysis and machine learning methods to facilitate the interpretation and promotion of an archaeological ceramic heritage. It consists in implementing a 3D digit...
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ISBN:
(纸本)9781479986378
the ARCADIA project aims at developing automatic image analysis and machine learning methods to facilitate the interpretation and promotion of an archaeological ceramic heritage. It consists in implementing a 3D digitalization chain of the discovered shards to extract the decoration imprinted by the potters using a carved wood wheel. the characterization of the hollow pattern from a binary map given by the 3D image then allows the automatic classification of these patterns. We propose here a feasibility study by comparing the results of automatic classification from the manual inkings made by archaeologists and those from 3D digitalizations of the same corpus of shards.
the proceedings contain 11 papers. the topics discussed include: motif discovery for proteins using subsequence clustering;graphical models of residue coupling in protein families;computational approaches for bridging...
ISBN:
(纸本)1595932135
the proceedings contain 11 papers. the topics discussed include: motif discovery for proteins using subsequence clustering;graphical models of residue coupling in protein families;computational approaches for bridging genomics and health;predicting cancer susceptibility from single nucleotide polymorphism data: a case study in multiple myeloma;accelerating DNA sequencing-by- hybridization with noise;on discovery of maximal confident rules without support pruning in microarray data;a data-mining approach to cell population de-convolution from gene expressions using particle filters;siRNA off-target search: a hybrid q-gram based filtering approach;analysis of protein-protein interaction networks using random walks;finding cliques in protein interaction networks via transitive closure of a weighted graph;and boosting performance of bio-entity recognition by combining results from multiple systems.
Accurate detection of lip contour is important in many application areas, including biometric authentication, human computer interaction, and facial expression recognition. In this paper, we propose a new lip boundary...
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this contribution introduces a new concept to analyze the manual order picking process which is a key task in the field of logistics. the approach relies on a sensor-based motion classification already used in other d...
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Neural network system is a self - learning adaptive system, and it is easy to associate, synthesize and generalize with its properties of fault - tolerance and robustness. therefore, it is available to process the pat...
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ISBN:
(纸本)9781424404759
Neural network system is a self - learning adaptive system, and it is easy to associate, synthesize and generalize with its properties of fault - tolerance and robustness. therefore, it is available to process the pattern information, which is hard to describe with language. In consideration of the shortage of Fuzzy theory and the advantage of vague set, that is Fuzzy membership function has only one single value;it cannot get more reasonable classified and cognizable results. While vague sets' distinguishing feature is having two values which present both of the opposite factors to deal with nonlinearities and uncertain system. In this paper, we define new fuzzy neurons and propose the structure of Vague Neural Network (VNN), and then we expounded the recognition method based on it.
In this paper, a new, multiscale wavelet support vector machines model (MWSVM) is proposed, according to the Mercer condition, the wavelet frame theory and kernel function nature. From the statistical learning theory ...
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ISBN:
(纸本)9781424410651
In this paper, a new, multiscale wavelet support vector machines model (MWSVM) is proposed, according to the Mercer condition, the wavelet frame theory and kernel function nature. From the statistical learning theory and the SVM model, pointed out the SVM essence is kernel method, the different kernel function has decided the different SVM. the choice of kernel parameters is simplified in MWSVM. By the experiment withthe single-variable two-variable function and real image, the new model can approach linear and the non-linear combination functions very well. the experimental result shows that MWSVM is the validity and the usability.
It is very important for communication equipment to realize the recognition and prediction of jamming signals in a short time. In the communication environment with variable jamming mode and noise, it is very difficul...
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Gait information can be used to identify and track persons. this work proposes a new gait identification method aggregating multiple features observed by a motion capture sensor and evaluates the robustness against ob...
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ISBN:
(纸本)9789897583599
Gait information can be used to identify and track persons. this work proposes a new gait identification method aggregating multiple features observed by a motion capture sensor and evaluates the robustness against obstacles in walking. the simplest gait identification is to use gait statistics, but these are not a significant feature with regard to identifying people accurately. Hence, in this work, we use the dynamic time warping (DTW) algorithm to calculate distances of gait sequences. DTW is a pattern-matching algorithm mainly used in speech recognition. It can compare two sets of time series data, even when they have different lengths. We also propose an optimal feature integration method for DTW distances. For evaluating the proposed method, we developed a prototype system and calculated the equal error rate (EER) using 31 subjects. As a result, we clarified that the EER of the proposed method is 0.036 for normal walking, and that it is robust to some obstacles in walking.
Latent fingerprints captured at the crime scene plays significant role as an evidence to capture the criminals. As latent fingerprints are the accidently left skin impressions, so these are found to be with broken rid...
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ISBN:
(纸本)9781509035434
Latent fingerprints captured at the crime scene plays significant role as an evidence to capture the criminals. As latent fingerprints are the accidently left skin impressions, so these are found to be with broken ridge composition, overlapped patterns and spoiled minutiae information. there latent fingerprint are of no use until the reconstruction & enhancement of their ridges, quality and minutiae information. Manual reconstruction, enhancement and recognition of latent fingerprints is much expensive, dull and time overriding procedure. So, Researchers are continuously working to design an autonomous latent fingerprint recognition system but facing various challenges like availability of spoiled ridges, less information & background noise, lack of publicly availability of latent fingerprint dataset and non-availability of any specific method for fingerprint matching. In this paper, an analytical framework is presented for the reconstruction, enhancement and recognition of latent fingerprints. Initially hybrid approach of Exemplar Inpainting and Partial Differential Equation is applied for the reconstruction of spoiled ridges. Enhancement is performed to reduce the noise value and final matching is performed using binarisation approach to recognize the criminals. the proposed concept is tested for the dataset of NIST SD-27 database withthe evaluation parameters of False Acceptance Rate and Genuine Acceptance Rate.
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