39 resultados para Stereo matching


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Corn and soyabeans may not be available in many countries particularly those which do not have sufficient foreign currency or the capacity to grow them. This paper outlines strategies that may be important under these circumstances. Alternative feedstuffs and various feeding systems may be used to support poultry production. Alternative ingredients such as rice bran, pearl millet, cottonseed meal and grain legumes are discussed. Evidence is presented showing that amino acid requirements of layers and broilers may be too generous particularly in countries where climate, management and disease can impose production constraints. The ability of finishing broilers to perform well on very low-energy diets allows the inclusion of alternative feeds and by-products into formulations. Very low protein diets based on cereals and free amino acids can be used for layers without loss of performance. Self-selection of feedstuffs may be an important strategy in reducing feed costs of broilers and layers. The concept of matching production with available feed resources may compromise broiler growth and egg production, but in many countries this may be the most economical choice. Countries in the humid tropics usually have reduced poultry performance. The effects of high temperature and humidity are difficult to overcome. The vexed questions of the escalation in the price of fossil fuel and the outbreak of avian influenza, both seemingly without a solution, are clouds hanging over an otherwise buoyant industry.

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In inflammatory disorders (e.g. psoriasis), local concentrations of human neutrophil elastase (HNE), also known as polymorphonuclear leukocyte elastase (HLE), possibly overwhelm its natural inhibitors leading to extracellular matrix degradation. Elevated levels of HNE have been reported in a variety of inflammatory disorders, including psoriasis. Peptidic HNE inhibitors have a common hydrophobic sequence (Ala-Ala-Pro-Val). This peptide sequence inhibits HNE competitively; however the stratum corneum presents an effective barrier to the delivery of this tetrapeptide across the skin. The current work investigates the delivery of the modified peptide whereby the tetrapeptide was lipidated to enhance its ability to penetrate the stratum The tetrapeptide Was Coupled to a racaemic mixture of a short chain lipoamino acid (LAA) resulting in two diastereomers of the lipoamino acid-modified tetrapeptide. The penetration of the lipopeptide mixture was assessed across human epidermis in vitro. The percentage of applied dose penetrating to the receptor over 8 h following administration was 2.53% for the D-LAA conjugate and 1.47% for the L-diastereomer, compared to 0% for the peptide. The D-diastereomer appears to be relatively stable but the L-diastereomer appears to degrade releasing possibly the tetrapeptide and peptide fragment(s). Therefore the results clearly indicate that coupling the tetrapeptide to a short chain LAA enhances its delivery across human epidermis.

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The edge-to-edge matching model, which was originally developed for predicting crystallographic features in diffusional phase transformations in solids, has been used to understand the formation of in-plane textures in TiSi2 (C49) thin films on Si single crystal (001)si surface. The model predicts all the four previously reported orientation relationships between C49 and Si substrate based on the actual atom matching across the interface and the basic crystallographic data only. The model has strong potential to be used to develop new thin film materials. (c) 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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An approach and strategy for automatic detection of buildings from aerial images using combined image analysis and interpretation techniques is described in this paper. It is undertaken in several steps. A dense DSM is obtained by stereo image matching and then the results of multi-band classification, the DSM, and Normalized Difference Vegetation Index (NDVI) are used to reveal preliminary building interest areas. From these areas, a shape modeling algorithm has been used to precisely delineate their boundaries. The Dempster-Shafer data fusion technique is then applied to detect buildings from the combination of three data sources by a statistically-based classification. A number of test areas, which include buildings of different sizes, shape, and roof color have been investigated. The tests are encouraging and demonstrate that all processes in this system are important for effective building detection.

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We consider the statistical problem of catalogue matching from a machine learning perspective with the goal of producing probabilistic outputs, and using all available information. A framework is provided that unifies two existing approaches to producing probabilistic outputs in the literature, one based on combining distribution estimates and the other based on combining probabilistic classifiers. We apply both of these to the problem of matching the HI Parkes All Sky Survey radio catalogue with large positional uncertainties to the much denser SuperCOSMOS catalogue with much smaller positional uncertainties. We demonstrate the utility of probabilistic outputs by a controllable completeness and efficiency trade-off and by identifying objects that have high probability of being rare. Finally, possible biasing effects in the output of these classifiers are also highlighted and discussed.

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The orientation relationship (OR) between the beta(Zn) phase and the alpha(Al) phase and the corresponding habit planes in a Zn-Al eutectoid alloy were accurately determined using convergent beam Kikuchi line diffraction patterns. In addition to the previously reported OR. [11 (2) over bar0](beta)parallel to[110](alpha), (0002)(beta)parallel to ((1) over bar 11)alpha, two new ORs were observed. They are: [11 (2) over bar0](beta)parallel to [110], ((1) over bar 101)(beta) 0.82 degrees from (002)(alpha) and [(1) over bar 100](beta)parallel to[112](alpha), (0002)(beta) 4.5 degrees from (111)(alpha). These ORs can be explained and understood using the recently developed edge-to-edge matching model. (c) 2006 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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Vocal mimicry provides a unique system for investigating song learning and cultural evolution in birds. Male lyrebirds produce complex vocal displays that include extensive and accurate mimicry of many other bird species. We recorded and analysed the songs of the Albert's lyrebird (Menura alberti) and its most commonly imitated model species, the satin bowerbird (Ptilonorhynchus violaceus), at six sites in southeast Queensland, Australia. We show that each population of lyrebirds faithfully reproduces the song of the local population of bowerbirds. Within a population, lyrebirds show less variation in song structure than the available variation in the songs of the models. These results provide the first quantitative evidence for dialect matching in the songs of two species that have no direct ecological relationship.

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The basis of the present authors' edge-to-edge matching model for understanding the crystallography of partially coherent precipitates is the minimization of the energy of the interface between the two phases. For relatively simple crystal structures, this energy minimization occurs when close-packed, or relatively close-packed, rows of atoms match across the interface. Hence, the fundamental principle behind edge-to-edge matching is that the directions in each phase that correspond to the edges of the planes that meet in the interface should be close-packed, or relatively close-packed, rows of atoms. A few of the recently reported examples of what is termed edge-to-edge matching appear to ignore this fundamental principle. By comparing theoretical predictions with available experimental data, this article will explore the validity of this critical atom-row coincidence condition, in situations where the two phases have simple crystal Structures and in those where the precipitate has a more complex structure.

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An emerging issue in the field of astronomy is the integration, management and utilization of databases from around the world to facilitate scientific discovery. In this paper, we investigate application of the machine learning techniques of support vector machines and neural networks to the problem of amalgamating catalogues of galaxies as objects from two disparate data sources: radio and optical. Formulating this as a classification problem presents several challenges, including dealing with a highly unbalanced data set. Unlike the conventional approach to the problem (which is based on a likelihood ratio) machine learning does not require density estimation and is shown here to provide a significant improvement in performance. We also report some experiments that explore the importance of the radio and optical data features for the matching problem.

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One of critical challenges in automatic recognition of TV commercials is to generate a unique, robust and compact signature. Uniqueness indicates the ability to identify the similarity among the commercial video clips which may have slight content variation. Robustness means the ability to match commercial video clips containing the same content but probably with different digitalization/encoding, some noise data, and/or transmission and recording distortion. Efficiency is about the capability of effectively matching commercial video sequences with a low computation cost and storage overhead. In this paper, we present a binary signature based method, which meets all the three criteria above, by combining the techniques of ordinal and color measurements. Experimental results on a real large commercial video database show that our novel approach delivers a significantly better performance comparing to the existing methods.