Single-image Tomography: 3D Volumes from 2D Cranial X-Rays

As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of data created when extending the 2D image into a 3D volume, we suggest firstly to learn a coarse, fixed-resolution volume which is then fused in a second step with the input x-ray into a high-resolution volume. To train and validate our approach we introduce a new dataset that comprises of close to half a million computer-simulated 2D x-ray images of 3D volumes scanned from 175 mammalian species. Applications of our approach include stereoscopic rendering of legacy x-ray images, re-rendering of x-rays including changes of illumination, view pose or geometry. Our evaluation includes comparison to previous tomography work, previous learning methods using our data, a user study and application to a set of real x-rays

Self-Supervised Shape and Appearance Modeling via Neural Differentiable Graphics

Inferring 3D shape and appearance from natural images is a fundamental challenge in computer vision. Despite recent progress using deep learning methods, a key limitation is the availability of annotated training data, as acquisition is often very challenging and expensive, especially at a large scale. This thesis proposes to incorporate physical priors into neural networks that allow for self-supervised learning. As a result, easy-to-access unlabeled data can be used for model training. In particular, novel algorithms in the context of 3D reconstruction and texture/material synthesis are introduced, where only image data is available as supervisory signal. First, a method that learns to reason about 3D shape and appearance solely from unstructured 2D images, achieved via differentiable rendering in an adversarial fashion, is proposed. As shown next, learning from videos significantly improves 3D reconstruction quality. To this end, a novel ray-conditioned warp embedding is proposed that aggregates pixel-wise features from multiple source images. Addressing the challenging task of disentangling shape and appearance, first a method that enables 3D texture synthesis independent of shape or resolution is presented. For this purpose, 3D noise fields of different scales are transformed into stationary textures. The method is able to produce 3D textures, despite only requiring 2D textures for training. Lastly, the surface characteristics of textures under different illumination conditions are modeled in the form of material parameters. Therefore, a self-supervised approach is proposed that has no access to material parameters but only flash images. Similar to the previous method, random noise fields are reshaped to material parameters, which are conditioned to replicate the visual appearance of the input under matching light

Measuring Meritocracy: A framework for investigation

What is meritocracy? Those left behind by systems claiming to be meritocratic, and those interested in their fate, have called the possibility of a fair meritocracy into question, and recently these calls have gotten louder. Our driving conviction behind the project is the idea that much of the disagreements stem from the ambiguity in the term, and that this ambiguity is perpetrated because it has never been measured or even operationalized. We spend the first two sections distilling the definition and tensions. We position our definition between the critics who view it as the modern version of “Just World Hypothesis” and the proponents who hope to have solved issues of distributive and allocative justice once and for all. We find quickly that complete meritocracies are nonexistent (and not interesting to our purposes), and that the best working definition is that of a negative composite view of meritocratic processes in an industry. The strength of our negative model lies in measuring the weight of all the factors that should not have been of influence in moving from one stage to the next, had the process been meritocratic, minimizing confounding and selection bias. After introducing the operationalized form, we use structural equation modeling to apply our measurement to the medical and military industries in the United States. We find that elements contributing to a career process are best analyzed as discrete points: this lets us make more valuable statements than “the coding world is extremely meritocratic” or “people from poor socioeconomic backgrounds have worse career prospects” and identify the point where factors of convergence would have the biggest effect

Global analysis of the determinants of systemic risk during the Global Financial Crisis of 2008 and the European Sovereign Debt Crisis

This Dissertation aims to provide a differentiated answer to the research question “What drives banks’ contribution to systemic risk during periods of financial turmoil?” This research also distinguishes between contribution to local and contribution to global systemic risk in order to shed light on how banks’ contribution to systemic risk differs across various regions. A sample of international banks covering 39 countries is analyzed for this purpose. The selected crisis periods are the Global Financial Crisis around the collapse of Lehman Brothers in 2008, as well as the first and the second peak of the European Sovereign Debt Crisis in 2010 and 2011 respectively. Supporting conjectures from earlier risk literature, several bank-specific accounting variables are found to enable banks’ contribution to systemic risk during the Global Financial Crisis in 2008. More precisely, the size of a bank and its market-to-book ratio are found to be positively related to systemic risk while a bank’s profitability is found to be negatively related. In addition, more powerful regulatory supervisors are found to be negatively related to systemic risk while greater capital stringency imposed by regulators is found to be negatively related to systemic risk. However, most of the variables lose their statistical significance during the European Sovereign Debt Crisis, which supports previous findings suggesting that drivers of systemic risk vary over crisis periods and might even be unique to each crisis episode.Dissertação tem como objetivo fornecer uma resposta diferenciada à pergunta de pesquisa "Quais os determinantes da contribuição dos bancos para o risco sistémico durante períodos de instabilidade financeira?" Esta investigação efectua igualmente uma distinção entre contribuição para o risco sistémico local e global, a fim de esclarecer como é que a contribuição dos bancos para o risco sistémico difere nas várias regiões. É analisado, para este fim, uma amostra de bancos internacionais que abrange 39 países. Os períodos de crise selecionados são a Crise Financeira Global em torno do colapso da Lehman Brothers em 2008, assim como o primeiro e o segundo pico da Crise das Dívida Soberana europeia nos anos de 2010 e 2011, respetivamente. Como complemento das conjeturas da literatura de risco anteriormente elaboradas, várias variáveis contabilísticas específicas dos bancos influenciam a contribuição dos bancos para o risco sistémico durante a Crise Financeira Global de 2008. Mais precisamente, a dimensão do banco e o rácio ‘market-to-book’ do mercado bancário estão positivamente relacionados com o risco sistémico, enquanto que a rentabilidade de um banco está negativamente relacionada. Além disso, os supervisores regulatórios mais poderosos estão negativamente relacionados ao risco sistémico, embora o major rigor dos requisitos de capital impostos pelos reguladores também seja considerado estar negativamente relacionado ao risco sistémico. Contudo, a maior parte das variáveis perde a sua significância estatística durante a crise da Dívida Soberana europeia, o que suporta as descobertas científicas anteriores, que sugerem que os fatores de risco sistémico variam ao longo dos períodos de crise e possam até ser exclusivos para cada uma das crises

Montage as a gesture of mediation and education

Combining images, comparing and linking them in chains, clusters and texts is a cultural practice that was not invented with digitisation. It dates back to the nineteenth century, when the invention of photography facilitated the task of copying artworks and other cultural material, and putting them in different contexts. Later, with the invention of the moving image, the gesture of montage was developed as an entirely new device of narration and thinking. Alain Bergala refers to this cultural practice when he proposes, in The Cinema Hypothesis, the combination of film clips as a film-pedagogical praxis as well as a research method. This article investigates the theoretical, cultural and practical aspects of this method, in revisiting a wide range of writings by Jacques Rancière, Roland Barthes, André Malraux and Wsewolod Pudowkin, as well as materials from Aby Warburg’s Bilderatlas and the found footage film Why Don’t You Love Me? by Christoph Girardet and Matthias Müller (1999). Furthermore, by comparing an extract from Grigris by Mahamat-Saleh Haroun (2013) to Sandro Botticelli’s The Birth of Venus (1485/6), the didactic potential of this method is explored. The article thus considers the pedagogical, aesthetic, cultural and filmic aspects of the practice of ‘montage’ in its most basic sense: the combination of (audio)visual material

Political Gangsters: The Future of Racketeering Law in Politics Note

Racketeering law and election restrictions are two areas of law that are not typically connected. Previous to the landmark decision in Citizens United, the chances of finding racketeering within election law were probably very slim.The corruption created by this new ruling is a fear that the government has been trying to combat for over a century. Not only will the effects of this new rule increase the appearance of corruption, this corruption may rise to a criminal level if racketeering action actually takes place. The ever-changing and expanding definition of racketeering under the Racketeering Influenced and Corrupt Organizations Act shows us that including political activity in its list of offenses is not a far stretch--it is already actively being applied to many situations that were not intended in its passing. The immediate effects of this rule have already been seen in the political spending in the November 2010 midterm elections; these sorts of changes will likely take place in the next presidential election in 2012, but on a larger scale

Political Gangsters: The Future of Racketeering Law in Politics Note

Racketeering law and election restrictions are two areas of law that are not typically connected. Previous to the landmark decision in Citizens United, the chances of finding racketeering within election law were probably very slim.The corruption created by this new ruling is a fear that the government has been trying to combat for over a century. Not only will the effects of this new rule increase the appearance of corruption, this corruption may rise to a criminal level if racketeering action actually takes place. The ever-changing and expanding definition of racketeering under the Racketeering Influenced and Corrupt Organizations Act shows us that including political activity in its list of offenses is not a far stretch--it is already actively being applied to many situations that were not intended in its passing. The immediate effects of this rule have already been seen in the political spending in the November 2010 midterm elections; these sorts of changes will likely take place in the next presidential election in 2012, but on a larger scale