As one of main methods in modern steel production, welding plays a very important role in our national economy, which has been widely applied in many fields such as aviation, petroleum, chemicals, electricity, railways and so on. The craft of welding can be improved in terms of welding tools, welding technology and welding inspection. However, so far welding inspection has been a very complicated problem. Therefore, it is very important to effectively detect internal welding defects in the welded-structure part and it is worth to furtherly studying and researching.In this paper, the main task is research about the application of image segmentation in welding inspection. It is introduced that the image enhancement techniques and image segmentation techniques including image conversion, noise removal as well as threshold, clustering, edge detection and region extraction. Based on the MATLAB platform, it focuses on the application of image segmentation in ray detection of steeled-structure, found out the application situation of three different image segmentation method such as threshold, clustering and edge detection.Application of image segmentation is more competitive than image enhancement because that:1. Gray-scale based FCM clustering of image segmentation performs well, which can exposure pixels in terms of grey value level so as that it can show hierarchical position of related defects by grey value.2. Canny detection speeds also fast and performs well, that gives enough detail information around edges and defects with smooth lines.3. Image enhancement only could improve image quality including clarity and contrast, which can’t give other helpful information to detect welding defects.This paper comes from the actual needs of the industrial work and it proves to be practical at some extent. Moreover, it also demonstrates the next improvement direction including identification of welding defects based on the neural networks, and improved clustering algorithm based on the genetic ideas. / Program: Magisterutbildning i informatik

För att få en tydlig bild av en marknad använder företag sig av segmenteringstekniker för att dela upp konsumenter i olika segment med målet att kunna precisera sina marknadsföringsåtgärder och optimera sina försäljningsutsikter. I dagens globaliserade multikanalsamhälle suddas landsgränser ständigt ut, vilket skapar ett behov för företag att istället identifiera regionala marknader. Genom att karlägga regioner är det möjligt att röna ut om det även inom ett land kan finnas skillnader i attityder till olika varumärken. Kombinationen av geografisk, demografisk och psykografisk segmentering möjliggör för företag att inte enbart se vilken ålder konsumenter har eller vilken stad de bor i, utan även vilken typ av attityd de har gentemot en viss produkt eller ett varumärke.Studien syftar till att ta reda om det finns regionala skillnader i varumärkesattityder i Sverige samt vad attityderna grundar sig i. I form av en studie över tre geografiskt skilda områden i Sverige, där 239 respondenter medverkade i strukturerade intervjuer undersöktes om varumärkesattityder kan skilja sig åt i de olika regionerna. Vidare medverkade 6 personer i mer djupgående semistrukturerade intervjuer där kvalitativ information rörande skapande och förändring av varumärkesattityder kunnat inhämtas. Studien behandlar varumärkesattityder gentemot fallföretaget 8848 Altitude som är ett producerande företag med fokus på utrustning och konfektion för alpinsport. Det insamlade materialet analyserades med hjälp av ett antal teorier om segmentering, attityder och tribes.Studiens resultat visar på att det finns skillnader i varumärkesattityder över de olika regionerna i Sverige. Resultatet visar även att det inte enbart är geografisk och demografisk tillhörighet som avgör vilken attityd en konsument har gentemot ett varumärke. Däremot, helt oberoende av geografisk tillhörighet, är det möjligt att utröna data över en grupp respondenter som har likvärdig konsumtion, värderingar och användande av produkter vilket kan benämnas vid en tribe. Studiens slutsats menar att tribal tillhörighet är en aspekt som kan vara ett fördelaktigt tillägg i psykografisk segmentering. Genom att studera en eventuell tribe kan ett företag se vilka värden som länkar samman produkten med konsumenten och således precisera sin marknadsföring. / Program: Civilekonomprogrammet

Malignant melanoma is one of the most fatal forms of skin cancer. It has also become increasingly common, especially among white-skinned people exposed to the sun. Early detection of melanoma is essential to raise survival rates, since its detection at an early stage can be helpful and curable. Working out the dermoscopic clinical features (pigment network and lesion borders) of melanoma is a vital step for dermatologists, who require an accurate method of reaching the correct clinical diagnosis, and ensure the right area receives the correct treatment. These structures are considered one of the main keys that refer to melanoma or non-melanoma disease. However, determining these clinical features can be a time-consuming, subjective (even for trained clinicians) and challenging task for several reasons: lesions vary considerably in size and colour, low contrast between an affected area and the surrounding healthy skin, especially in early stages, and the presence of several elements such as hair, reflections, oils and air bubbles on almost all images. This thesis aims to provide an accurate, robust and reliable automated dermoscopy image analysis technique, to facilitate the early detection of malignant melanoma disease. In particular, four innovative methods are proposed for region segmentation and classification, including two for pigmented region segmentation, one for pigment network detection, and one for lesion classification. In terms of boundary delineation, four pre-processing operations, including Gabor filter, image sharpening, Sobel filter and image inpainting methods are integrated in the segmentation approach to delete unwanted objects (noise), and enhance the appearance of the lesion boundaries in the image. The lesion border segmentation is performed using two alternative approaches. The Fuzzy C-means and the Markov Random Field approaches detect the lesion boundary by repeating the labeling of pixels in all clusters, as a first method. Whereas, the Particle Swarm Optimization with the Markov Random Field method achieves greater accuracy for the same aim by combining them in the second method to perform a local search and reassign all image pixels to its cluster properly. With respect to the pigment network detection, the aforementioned pre-processing method is applied, in order to remove most of the hair while keeping the image information and increase the visibility of the pigment network structures. Therefore, a Gabor filter with connected component analysis are used to detect the pigment network lines, before several features are extracted and fed to the Artificial Neural Network as a classifier algorithm. In the lesion classification approach, the K-means is applied to the segmented lesion to separate it into homogeneous clusters, where important features are extracted; then, an Artificial Neural Network with Radial Basis Functions is trained by representative features to classify the given lesion as melanoma or not. The strong experimental results of the lesion border segmentation methods including Fuzzy C-means with Markov Random Field and the combination between the Particle Swarm Optimization and Markov Random Field, achieved an average accuracy of 94.00% , 94.74% respectively. Whereas, the lesion classification stage by using extracted features form pigment network structures and segmented lesions achieved an average accuracy of 90.1% , 95.97% respectively. The results for the entire experiment were obtained using a public database PH2 comprising 200 images. The results were then compared with existing methods in the literature, which have demonstrated that our proposed approach is accurate, robust, and efficient in the segmentation of the lesion boundary, in addition to its classification.

This diploma thesis analyzes current book market, its specific features, history, threats and opportunities. The practical part deals with research and analysis of customer behaviour and their shopping habits. The research is then used for market segmentation.

O objetivo deste trabalho é apresentar uma técnica automática baseada em morfologia matemática para medida de sinal em imagens de cDNA desenvolvida no BIOINFO,em parceria com o Instituto Ludwig de Pesquisa contra o Câncer. A tecnologia de lâminas de cDNA é um processo baseado em hibridização que possibilita observar a concentração relativa de mRNA de amostras de tecidos analisando a luminosidade de sinais fluorescentes ou radioativos. Hibridização é o processo bioquímico onde duas fitas de ácido nucleico com seqüências complementares se combinam. A técnica apresentada permite o cálculo da expressão gênica com alto grau de automação, podendo o usuário corrigir com facilidade eventuais erros de segmentação. O usuário interage com o programa apenas para selecionar as imagens e inserir os dados de geometria da lâmina. A estratégia de solução usada tem três fases: gradeamento dos blocos, gradeamento dos spots e segmentação dos spots. Todas as fases utilizam filtros morfológicos e as fases de gradeamento possuem um passo final de correção baseado nos dados de geometria da lâmina o que aumenta a robustez do processo, que funciona bem mesmo em imagens ruidosas. / The objective of this work is to present the automated technique for measuring signal from cDNA images developed in BIOINFO, associated with the Ludwig Institute for Cancer Research. Microarray technology is a hybridization based process that makes possible to quantify the relative abundance of mRNA in two tissue samples analysing the luminosity of fluorescent or radioactive signals. Hybridization is a biochemical process where a strand of nucleic acid matches up its counterpart. The developed technique permits the calculation of gene expression with a high level of automation. Besides that, the user can easily correct eventual segmentation mistakes. The user interacts with the program only to select the images and to set the slide geometry parameters. The solution strategy has three main steps: subarray griding, spots gridding and spots detection. All the steps use morphological filters, and the two gridding steps have a final correction substep based on the slide geometry, increasing the process robustness, that works well even in noisy images.

O estudo é uma sistematização do tema Segmentação de Clientes aplicada em bibliotecas. Seu objetivo é demonstrar como a Segmentação de Clientes contribui para uma gestão efetiva de Marketing na biblioteca auxiliando no desenvolvimento de produtos e ações; potencializando os seus resultados. Compõe-se de duas partes: a primeira, um levantamento bibliográfico buscando identificar as tipologias de Segmentação de Clientes existentes, tanto no Marketing quanto na biblioteca, além de cases internacionais com a aplicação da estratégia nesse ambiente; a segunda, uma demonstração de como essa estratégia, e os passos que a antecedem no processo de gestão de Marketing, pode contribuir para potencializar as ações e os produtos e serviços da biblioteca. Para essa demonstração foi utilizado como referência o modelo sistêmico de gestão de Marketing desenvolvido pelo Profº. Dr. Mitsuru Yanaze transpondo-o para uma situação hipotética de uma biblioteca especializada corporativa da área de Marketing. O exercício desenvolvido, além de contextualizar a estratégia de Segmentação no processo de gestão e indicar os benefícios conseguidos com a sua adoção, contribui para diferenciar Marketing e promoção, usados habitualmente como sinônimos. / The study is a systematization of the subject Client Segmentation used in libraries. Its aim is to demonstrate how the Client Segmentation contributes to an effective Marketing management in library, promoting the development of products, Marketing actions and leveraging their results. This is a two parts study: the first, a bibliographic review to identify different Segmentation categories either in Marketing as well as in libraries, there are also international cases with this segmentation strategy applied to libraries; the second part is to show how the strategy of Segmentation and the steps taken before its application can contribute to make the library products and its services to be successful. To demonstrate how this can be achieved, a management model, developed by Professor Mitsuru Yanaze, was used and transposed to simulate a management situation in a Marketing corporate library. This hypothetical situation contributed to contextualize Segmentation strategy in management process, which can help librarians to better understand its benefits. Furthermore, this study helped to explain that Marketing differs from promotion; usually mistaken as synonyms.

Image understanding is the task of interpreting images by effectively solving the individual tasks of object recognition and semantic image segmentation. An image understanding system must have the capacity to distinguish between similar looking image regions while being invariant in its response to regions that have been altered by the appearance-altering transformation. The fundamental challenge for any such system lies within this simultaneous requirement for both invariance and specificity. Many image understanding systems have been proposed that capture geometric properties such as shapes, textures, motion and 3D perspective projections using filtering, non-linear modulus, and pooling operations. Deep learning networks ignore these geometric considerations and compute descriptors having suitable invariance and stability to geometric transformations using (end-to-end) learned multi-layered network filters. These deep learning networks in recent years have come to dominate the previously separate fields of research in machine learning, computer vision, natural language understanding and speech recognition. Despite the success of these deep networks, there remains a fundamental lack of understanding in the design and optimization of these networks which makes it difficult to develop them. Also, training of these networks requires large labeled datasets which in numerous applications may not be available. In this dissertation, we propose the ScatterNet Hybrid Framework for Deep Learning that is inspired by the circuitry of the visual cortex. The framework uses a hand-crafted front-end, an unsupervised learning based middle-section, and a supervised back-end to rapidly learn hierarchical features from unlabelled data. Each layer in the proposed framework is automatically optimized to produce the desired computationally efficient architecture. The term `Hybrid' is coined because the framework uses both unsupervised as well as supervised learning. We propose two hand-crafted front-ends that can extract locally invariant features from the input signals. Next, two ScatterNet Hybrid Deep Learning (SHDL) networks (a generative and a deterministic) were introduced by combining the proposed front-ends with two unsupervised learning modules which learn hierarchical features. These hierarchical features were finally used by a supervised learning module to solve the task of either object recognition or semantic image segmentation. The proposed front-ends have also been shown to improve the performance and learning of current Deep Supervised Learning Networks (VGG, NIN, ResNet) with reduced computing overhead.

O estudo é uma sistematização do tema Segmentação de Clientes aplicada em bibliotecas. Seu objetivo é demonstrar como a Segmentação de Clientes contribui para uma gestão efetiva de Marketing na biblioteca auxiliando no desenvolvimento de produtos e ações; potencializando os seus resultados. Compõe-se de duas partes: a primeira, um levantamento bibliográfico buscando identificar as tipologias de Segmentação de Clientes existentes, tanto no Marketing quanto na biblioteca, além de cases internacionais com a aplicação da estratégia nesse ambiente; a segunda, uma demonstração de como essa estratégia, e os passos que a antecedem no processo de gestão de Marketing, pode contribuir para potencializar as ações e os produtos e serviços da biblioteca. Para essa demonstração foi utilizado como referência o modelo sistêmico de gestão de Marketing desenvolvido pelo Profº. Dr. Mitsuru Yanaze transpondo-o para uma situação hipotética de uma biblioteca especializada corporativa da área de Marketing. O exercício desenvolvido, além de contextualizar a estratégia de Segmentação no processo de gestão e indicar os benefícios conseguidos com a sua adoção, contribui para diferenciar Marketing e promoção, usados habitualmente como sinônimos. / The study is a systematization of the subject Client Segmentation used in libraries. Its aim is to demonstrate how the Client Segmentation contributes to an effective Marketing management in library, promoting the development of products, Marketing actions and leveraging their results. This is a two parts study: the first, a bibliographic review to identify different Segmentation categories either in Marketing as well as in libraries, there are also international cases with this segmentation strategy applied to libraries; the second part is to show how the strategy of Segmentation and the steps taken before its application can contribute to make the library products and its services to be successful. To demonstrate how this can be achieved, a management model, developed by Professor Mitsuru Yanaze, was used and transposed to simulate a management situation in a Marketing corporate library. This hypothetical situation contributed to contextualize Segmentation strategy in management process, which can help librarians to better understand its benefits. Furthermore, this study helped to explain that Marketing differs from promotion; usually mistaken as synonyms.

Les entrepôts de la logistique, secteur charnière entre production et consommation, ne produisent pas une marchandise en particulier, mais un flux de marchandises. Partant du constat que le secteur, en forte croissance ces dernières années, a été le plus souvent étudié par les sciences sociales de manière globale, l’objectif de la thèse est d’analyser de manière intensive deux entrepôts logistiques appartenant à la même entreprise dans deux contextes nationaux et régionaux différents, le nord-est de l’Italie et la région parisienne. Plusieurs interrogations traversent cette enquête. Comment les entreprises multinationales de logistique s’adaptent-elles au contexte juridique, économique et social dans lequel elles opèrent et comment participent-elles à le transformer ? Quels sont les personnels mobilisés ? Quelles sont leurs conditions et pratiques de travail ? L’analyse porte donc sur l’organisation du travail, sur les effets des politiques de recrutement et de gestion sur les expériences sociales des ouvriers migrants et locaux, sur les interactions entre salariés et entre groupes, ainsi que sur les pratiques de résistances formelles et informelles. La recherche s’appuie sur une enquête ethnographique dans les deux entrepôts, ainsi que sur une série d’entretiens biographiques. La thèse se situe au croisement d’une sociologie du travail et d’une sociologie des organisations, d’une sociologie des mobilisations collectives et de la segmentation du marché de l’emploi, d’une sociologie des classes populaires, et plus secondairement d’une sociologie des espaces urbains. / Zipper between production and consumption, the logistics warehouses, rather than a specific good, product a flow of commodities. The sector has been growing fastly in the last years, and it is usually studied from a global perspective within social sciences. The aim of this thesis is to elaborate an in depth analysis on two warehouses of the same multinational logistics company within two distinct national and regional contexts: the Italian North-East and the Paris metropolis. The thesis is structured around many research questions: How do the logistics multinational companies adapt to the juridical, economic, and social context where they operate? How do they contribute to its transformation? Which recruitment policies do they apply? What are the practices and the working conditions? The analysis is then focused on the organization of the labour process, on the specific effects that the recruitment policies and the labour-force management produce on the social experiences of local and migrant workers, on the interactions and relationships between groups within the workplace, as well as on the formal and informal resistance practices played by the workers. The research is based on an ethnographic enquiry inside the two warehouses and on a series of biographic interviews. The thesis is at the crossroad between different sociological approaches: sociology of work and organizations, collective mobilizations and the segmentation of labour market, popular classes and, to a lesser extent, sociology of urban spaces.

Deep Learning is dominant in the field of computer vision, thanks to its high performance. This high performance is driven by large annotated datasets and proper evaluation benchmarks. However, two important areas in computer vision, depth-based hand segmentation, and local features, respectively lack a large well-annotated dataset and a benchmark protocol that properly demonstrates its practical performance. Therefore, in this thesis, we focus on these two problems. For hand segmentation, we create a novel systematic way to easily create automatic semantic segmentation annotations for large datasets. We achieved this with the help of traditional computer vision techniques and minimal hardware setup of one RGB-D camera and two distinctly colored skin-tight gloves. Our method allows easy creation of large-scale datasets with high annotation quality. For local features, we create a new modern benchmark, that reveals their different aspects. Specifically wide-baseline stereo matching and Multi-View Stereo (MVS), of keypoints in a more practical setup, namely Structure-from-Motion (SfM). We believe that through our new benchmark, we will be able to spur research on learned local features to a more practical direction. In this respect, the benchmark developed for the thesis will be used to host a challenge on local features. / Graduate