A new method for videoconferencing using the concept of spatially varying sensing is introduced. Various techniques are discussed for combining information obtained from multiple points-of-interest (foveae) in an imag...
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We have compared and improved several implementations of the Wiener filter to remove noise effects from Scanning Tunneling Microscope images. We have found that the implementation of Weisman et al. [6], using the nois...
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Graph grammars provide a useful formalism for describing structural manipulations of multi-dimensional data. We briefly review theoretical aspects of graph grammars, particularly of the embedding problem, and then sum...
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Finding patterns in time series of images requires dedicated approaches for the analysis, in the setup of the experiment, the image analysis as well as in the patternrecognition. the large volume of images that are u...
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ISBN:
(纸本)9783642248542
Finding patterns in time series of images requires dedicated approaches for the analysis, in the setup of the experiment, the image analysis as well as in the patternrecognition. the large volume of images that are used in the analysis necessitates an automated setup. In this paper, we illustrate the design and implementation of such a system for automated analysis from which phenotype measurements can be extracted for each object in the analysis. Using these measurements, objects are characterized into phenotypic groups through classification while each phenotypic group is analyzed individually. the strategy that is developed for the analysis of time series is illustrated by a case study on EGFR endocytosis. Endocytosis is regarded as a mechanism of attenuating epidermal growth factor receptor (EGFR) signaling and of receptor degradation. Increasingly, evidence becomes available showing that cancer progression is associated with a defect in EGFR endocytosis. Functional genomics technologies combine high-throughput RNA interference with automated fluorescence microscopy imaging and multi-parametric image analysis, thereby enabling detailed insight into complex biological processes, like EGFR endocytosis. the experiments produce over half a million images and analysis is performed by automated procedures. the experimental results show that our analysis setup for high-throughput screens provides scalability and robustness in the temporal analysis of an EGFR endocytosis model.
Facial occlusions such as eyeglasses, hairs and beards decrease the performance of face recognition algorithms. To improve the performance of face recognition algorithms, this paper proposes a novel framework of face ...
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ISBN:
(纸本)9781479903108
Facial occlusions such as eyeglasses, hairs and beards decrease the performance of face recognition algorithms. To improve the performance of face recognition algorithms, this paper proposes a novel framework of face recognition combined withthe occluded-region detection method. In this paper, we detect occluded regions using Fast-Weighted Principal Component Analysis (FW- PCA) and use the occluded regions as weights for matching face images. To demonstrate the effectiveness of the proposed framework, we use two face recognition algorithms: Local Binary patterns (LBP) and Phase-Only Correlation (POC). Experimental evaluation using public face image databases indicates performance improvement of the face recognition algorithms for face images with natural and artificial occlusions.
In research labs, there is often a need to customise software at every step in a given bioinformatics workflow, but traditionally it has been difficult to obtain both a high degree of customisability and good performa...
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ISBN:
(纸本)9783642341236
In research labs, there is often a need to customise software at every step in a given bioinformatics workflow, but traditionally it has been difficult to obtain both a high degree of customisability and good performance. Performance-sensitive tools are often highly monolithic, which can make research difficult. We present a novel set of software development principles and a bioinformatics framework, Friedrich, which is currently in early development. Friedrich applications support both early stage experimentation and late stage batch processing, since they simultaneously allow for good performance and a high degree of flexibility and customisability. these benefits are obtained in large part by basing Friedrich on the multiparadigm programming language Scala. We present a case study in the form of a basic genome assembler and its extension with new functionality. Our architecture(1) has the potential to greatly increase the overall productivity of software developers and researchers in bioinformatics.
A system for the classification of real 3-D objects is presented. Ten objects are presented in arbitrary orientation (and position, within limits). the perception of an object is achieved by the use of multiple stereo...
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the proceedings contain 37 papers. the topics discussed include: bipartite graph matching for computing the edit distance of graphs;matching of tree structures for registration of medical images;graph-based methods fo...
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ISBN:
(纸本)9783540729020
the proceedings contain 37 papers. the topics discussed include: bipartite graph matching for computing the edit distance of graphs;matching of tree structures for registration of medical images;graph-based methods for retinal mosaicing and vascular characterization;graph based shapes representation and recognition;a continuous-based approach for partial clique enumeration;a bound for non-subgraph isomorphism;a correspondence measure for graph matching using the discrete quantum walk;a quadratic programming approach to the graph edit distance problem;image classification using marginalized kernels for graphs;comparing sets of 3D digital shapes through topological structures;hierarchy construction schemes within the scale set framework;local reasoning in fuzzy attribute graphs for optimizing sequential segmentation;and graph-based perceptual segmentation of stereo vision 3D images at multiple abstraction levels.
the proceedings contain 27 papers. the special focus in this conference is on Artificial Neural Networks for patternrecognition. the topics include: Large margin distribution learning;a decorrelation approach for pru...
ISBN:
(纸本)9783319116556
the proceedings contain 27 papers. the special focus in this conference is on Artificial Neural Networks for patternrecognition. the topics include: Large margin distribution learning;a decorrelation approach for pruning of multilayer perceptron networks;unsupervised active learning of CRF model for cross-lingual named entity recognition;incremental feature selection by block addition and block deletion using least squares SVRs;low-dimensional data representation in data analysis;analyzing dynamic ensemble selection techniques using dissimilarity analysis;hidden Markov models based on generalized Dirichlet mixtures for proportional data modeling;majority-class aware support vector domain oversampling for imbalanced classification problems;forward and backward forecasting ensembles for the estimation of time series missing data;dynamic weighted fusion of adaptive classifier ensembles based on changing data streams;combining bipartite graph matching and beam search for graph edit distance approximation;computing upper and lower bounds of graph edit distance in cubic time;a new multi-class fuzzy support vector machine algorithm;a reinforcement learning algorithm to train a Tetris playing agent;automatic bridge crack detection - a texture analysis-based approach;part-based high accuracy recognition of serial numbers in bank notes;comparative study of feature selection for white blood cell differential counts in low resolution images;end-shape recognition for Arabic handwritten text segmentation;intelligent ensemble systems for modeling NASDAQ microstructure;face recognition based on discriminative dictionary with multilevel feature fusion;investigating of preprocessing techniques and novel features in recognition of handwritten Arabic characters and a time series classification approach for motion analysis using ensembles in ubiquitous healthcare systems.
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