The recovery of generic solid parts is a fundamental step towards the realization of general-purpose vision systems. This thesis investigates issues in grouping, segmentation and recognition of parts from two-dimensional edge images. A new paradigm of part-based grouping of features is introduced that bridges the classical grouping and model-based approaches with the purpose of directly recovering parts from real images, and part-like models are used that both yield low theoretical complexity and reliably recover part-plausible groups of features. The part-like models used are statistical point distribution models, whose training set is built using random deformable superellipse. The computational approach that is proposed to perform model-guided part-based grouping consists of four distinct stages. In the first stage, codons, contour portions of similar curvature, are extracted from the raw edge image. They are considered to be indivisible image features because they have the desirable property of belonging either to single parts or joints. In the second stage, small seed groups (currently pairs, but further extension are proposed) of codons are found that give enough structural information for part hypotheses to be created. The third stage consists in initialising and pre-shaping the models to all the seed groups and then performing a full fitting to a large neighbourhood of the pre-shaped model. The concept of pre-shaping to a few significant features is a relatively new concept in deformable model fitting that has helped to dramatically increase robustness. The initialisations of the part models to the seed groups is performed by the first direct least-square ellipse fitting algorithm, which has been jointly discovered during this research; a full theoretical proof of the method is provided. The last stage pertains to the global filtering of all the hypotheses generated by the previous stages according to the Minimum Description Length criterion: the small number of grouping hypotheses that survive this filtering stage are the most economical representation of the image in terms of the part-like models. The filtering is performed by the maximisation of a boolean quadratic function by a genetic algorithm, which has resulted in the best trade-off between speed and robustness. Finally, images of parts can have a pronounced 3D structure, with ends or sides clearly visible. In order to recover this important information, the part-based grouping method is extended by employing parametrically deformable aspects models which, starting from the initial position provided by the previous stages, are fitted to the raw image by simulated annealing. These models are inspired by deformable superquadrics but are built by geometric construction, which render them two order of magnitudes faster to generate than in previous works. A large number of experiments is provided that validate the approach and, since several new issues have been opened by it, some future work is proposed.

Object classes are central to computer vision and have been the focus of substantial research in the last fifteen years. This thesis addresses the tasks of localizing entire objects in images (object class detection) and localizing their semantic parts (part detection). We present four contributions, two for each task. The first two improve existing object class detection techniques by using context and calibration. The other two contributions explore semantic part detection in weakly-supervised settings. First, the thesis presents a technique for predicting properties of objects in an image based on its global appearance only. We demonstrate the method by predicting three properties: aspect of appearance, location in the image and class membership. Overall, the technique makes multi-component object detectors faster and improves their performance. The second contribution is a method for calibrating the popular Ensemble of Exemplar- SVM object detector. Unlike the standard approach, which calibrates each Exemplar- SVM independently, our technique optimizes their joint performance as an ensemble. We devise an efficient optimization algorithm to find the global optimal solution of the calibration problem. This leads to better object detection performance compared to using independent calibration. The third innovation is a technique to train part-based model of object classes using data sourced from the web. We learn rich models incrementally. Our models encompass the appearance of parts and their spatial arrangement on the object, specific to each viewpoint. Importantly, it does not require any part location annotation, which is one of the main limits to training many part detectors. Finally, the last contribution is a study on whether semantic object parts emerge in Convolutional Neural Networks trained for higher-level tasks, such as image classification. While previous efforts studied this matter by visual inspection only, we perform an extensive quantitative analysis based on ground-truth part location annotations. This provides a more conclusive answer to the question.

Thesis (M.A.R.)--Emmanuel School of Religion, Johnson City, Tennessee, 2004. / Includes bibliographical references (leaves 55-58) and vita.

Abstract Taiwan¡¦s auto part manufacturer has achieved substantial technology levels due to long- term cooperation with domestic automakers and under the rule of vehicle local content rate requirement. Above all, some of auto part makers have the capability to export parts with their R&D over the recent years. Because Taiwan¡¦s vehicle market volume ranges from 340,000 to 510,000 , it virtually couldn¡¦t allow thousands of local automakers to achieve production economy-scale, leading to limited room for further development. As a result, local automakers seek to develop overseas markets. From 1992-2002, Ministry of Economic affairs aggressively seek Taiwan¡¦s accession to WTO to upgrade Taiwan¡¦s role as an major international trade player while helping Taiwan¡¦s auto part industry to gain access to international labor-division system. Finally, Taiwan became a member of WTO on 1st,Jan. 2002. However, the impact on Taiwan¡¦s accession to WTO would enable the market to project a ¡§¡¨winner take it all¡¨ situation. Because Taiwan¡¦s auto industry will face the impact of tariff reduction¡Bquota cancellation following Taiwan¡¦s admission to WTO and local content rate cancellation in Taiwan¡¦s auto part industry ,Taiwan¡¦s auto industry would face global competition ,which is not only a threat ,but an opportunity as well. On the other hand, Taiwan¡¦s admission to WTO would expand Taiwan¡¦s domain of international trade. The global market will open to us based on the principle of reciprocal benefit¡Bequality. It would be an advantage for us in the long term .Furthermore, the emerging auto markets ,such as China¡BASEAN, would also provide a big business opportunity for investment ,which would be beneficial to Taiwan¡¦s auto industry labor-division system and competitive advantage .However, the success of Taiwan auto part industry¡¦s transition depends on how auto parts suppliers seize opportunity , using and exploiting human resources¡B upgrading product design and development capability ¡B producing parts with quality that meets global standards¡Benhancing manufacturing technology ¡Bdeveloping marketing channels etc. Only by effectively integrating internal resources could we confront the impact and opportunities brought by our accession to WTO and grasp the opportunity to transition by utilizing successful management strategy. Key word: Auto part , policy, management strategy.

THESIS ABSTRACT The bulk of Internet Service Providers adopt two-part tariff. Two-part tariff means users should pay a fixed rental every month, and pay a varied fee base on their connecting hours. Internet Service Provider group their customers by analyzing customer¡¦s demand level, and provides different group different Pay-Rating. We call this situation Multiple Pay-Rating. If Internet Service Provider provide their customers single Pay-Rating. We call this situation Single Pay-Rating. People always analyze two-part tariff in monopoly market. In this thesis I will analyze two-part tariff in oligopoly market.Then compare with the former, and we will know whether two-part tariff erode customer¡¦s welfare. I will create a differentiate-product demand function base on Logit model, and build two-part tariff oligopoly competition model. Analyze the equilibrium in Single Pay-rating and in Multiple Pay-rating. And I drew several conclusions from the analysis. 1. In oligopoly market structure two-part tariff not necessarily deprive of customer¡¦s welfare. On the contrary if ISP group their customers, customer¡¦s welfare will improve. 2. If there are no differentiation between customers¡¦ utilities, nonlinear pricing will degraded to linear pricing. If customers¡¦ utilities are different, ISP will set up the unit connect fee equal to the unit cost, and the month rental will raised with the increasing differentiation between customers¡¦ utilities. 3. If Internet service provider group their customer and provide them different Pay-rating, the final equilibrium will be symmetrical equilibrium or non-symmetrical equilibrium.

Thesis--University of Michigan. / Vol. 2 contains the author's transcription of 24 madrigals for 4-8 voices into modern notation in score. Includes bibliographical references.

Thesis--University of Michigan. / Vol. 2 contains the author's transcription of 44 of De Rore's madrigals into modern notation in score. Includes bibliographical references.

This thesis mainly discusses a lexical category known by the name “classifier” or “measure” in Mandarin Chinese. According to Chinese descriptive grammars, which are followed in this thesis, there are at least two types of classifiers, nominal ones (classifiers for nouns) and verbal/ adverbial ones (classifiers for verbs). Within the category of classifiers, there is a subclass that is made of body part terms. Some of them are used for nouns (i.e., NCLs), some of them are used for verbs (i.e., VCLs), and many for both. The correlations between NCLs and VCLs are discussed in this thesis, especially the idea of how both types of classifier can provide delimitation to events. The semantic properties of VCLs and NCLs are explored in this thesis. The [Num+ CL+ N] construction is considered to be a NCLP (nominal classifier phrase) in this thesis and the [V+ [Num+CL]] construction is considered to be a VCLP. I will discuss VCLPs with respect to transitivity of verbs.

Thesis (M.C.S.)--Regent College, 1987. / Abstract. Vita. Bibliography: leaves 154-165.

Thesis (M.C.S.)--Regent College, 1987. / Abstract. Vita. Includes bibliographical references (leaves 154-165).