Deep Unsupervised Similarity Learning using Partially Ordered Sets

Unsupervised learning of visual similarities is of paramount importance to computer vision, particularly due to lacking training data for fine-grained similarities. Deep learning of similarities is often based on relationships between pairs or triplets of samples. Many of these relations are unreliable and mutually contradicting, implying inconsistencies when trained without supervision information that relates different tuples or triplets to each other. To overcome this problem, we use local estimates of reliable (dis-)similarities to initially group samples into compact surrogate classes and use local partial orders of samples to classes to link classes to each other. Similarity learning is then formulated as a partial ordering task with soft correspondences of all samples to classes. Adopting a strategy of self-supervision, a CNN is trained to optimally represent samples in a mutually consistent manner while updating the classes. The similarity learning and grouping procedure are integrated in a single model and optimized jointly. The proposed unsupervised approach shows competitive performance on detailed pose estimation and object classification.Comment: Accepted for publication at IEEE Computer Vision and Pattern Recognition 201

Unsupervised Video Understanding by Reconciliation of Posture Similarities

Understanding human activity and being able to explain it in detail surpasses mere action classification by far in both complexity and value. The challenge is thus to describe an activity on the basis of its most fundamental constituents, the individual postures and their distinctive transitions. Supervised learning of such a fine-grained representation based on elementary poses is very tedious and does not scale. Therefore, we propose a completely unsupervised deep learning procedure based solely on video sequences, which starts from scratch without requiring pre-trained networks, predefined body models, or keypoints. A combinatorial sequence matching algorithm proposes relations between frames from subsets of the training data, while a CNN is reconciling the transitivity conflicts of the different subsets to learn a single concerted pose embedding despite changes in appearance across sequences. Without any manual annotation, the model learns a structured representation of postures and their temporal development. The model not only enables retrieval of similar postures but also temporal super-resolution. Additionally, based on a recurrent formulation, next frames can be synthesized.Comment: Accepted by ICCV 201

Experiencias migratorias en indigenas purépechas en Nezahualcóyotl, Estado de México.

Este artículo tiene como fin reflexionar sobre el relato de vida de la población indígena y el migrante purépecha, que enfrenta procesos de cambio y continuidad cultural durante su arribo al municipio de Nezahualcóyotl Estado de México. El estudio es de carácter exploratorio por lo que no se conduce a conclusiones determinantes. Partimos de los planteamientos de Geertz (2005) para observar los procesos de significación social e incorporamos a Thomson (2006) para vislumbrar las estructuras de poder. Las evidencias muestran que los indígenas diseñan diversas estrategias que los colocan en una constante negociación y resistencia por preservar y resignificar su identidad indígena ante la vulnerabilidad, marginación y rechazo social del cual son sujetos. Se toma el caso de tres indígenas purépechas que habitan el municipio de Nezahualcóyotl, para desarrollar la interpretación en los cambios y continuidades de su identidad a partir de una serie de prácticas y estrategias que elaboran tanto de manera coercitiva como voluntaria.Este artículo tiene como fin reflexionar sobre el relato de vida de la población indígena y el migrante purépecha, que enfrenta procesos de cambio y continuidad cultural durante su arribo al municipio de Nezahualcóyotl Estado de México. El estudio es de carácter exploratorio por lo que no se conduce a conclusiones determinantes. Partimos de los planteamientos de Geertz (2005) para observar los procesos de significación social e incorporamos a Thomson (2006) para vislumbrar las estructuras de poder. Las evidencias muestran que los indígenas diseñan diversas estrategias que los colocan en una constante negociación y resistencia por preservar y resignificar su identidad indígena ante la vulnerabilidad, marginación y rechazo social del cual son sujetos. Se toma el caso de tres indígenas purépechas que habitan el municipio de Nezahualcóyotl, para desarrollar la interpretación en los cambios y continuidades de su identidad a partir de una serie de prácticas y estrategias que elaboran tanto de manera coercitiva como voluntaria.Universidad Nacional Autónoma de México Escuela Nacional de Trabajo Socia

Partial coherent states in graphene

Producción CientíficaWe employ a symmetric gauge to describe the interaction of electrons in graphene with a magnetic field which is orthogonal to the layer surface and to build the so-called partial and bidimensional coherent states for this system in the Barut-Girardello sense. We also evaluate the corresponding probability and current densities as well as the mean energy value.Junta de Castilla y León (projects VA137G18 and BU229P18)Ministerio de Economía, Industria y Competitividad (project MTM2014-57129-C2-1-P

On the design of an ECOC-compliant genetic algorithm

Genetic Algorithms (GA) have been previously applied to Error-Correcting Output Codes (ECOC) in state-of-the-art works in order to find a suitable coding matrix. Nevertheless, none of the presented techniques directly take into account the properties of the ECOC matrix. As a result the considered search space is unnecessarily large. In this paper, a novel Genetic strategy to optimize the ECOC coding step is presented. This novel strategy redefines the usual crossover and mutation operators in order to take into account the theoretical properties of the ECOC framework. Thus, it reduces the search space and lets the algorithm to converge faster. In addition, a novel operator that is able to enlarge the code in a smart way is introduced. The novel methodology is tested on several UCI datasets and four challenging computer vision problems. Furthermore, the analysis of the results done in terms of performance, code length and number of Support Vectors shows that the optimization process is able to find very efficient codes, in terms of the trade-off between classification performance and the number of classifiers. Finally, classification performance per dichotomizer results shows that the novel proposal is able to obtain similar or even better results while defining a more compact number of dichotomies and SVs compared to state-of-the-art approaches

Compressive strength degradation in ZrB2-based ultra-high temperature ceramic composites

The high temperature compressive strength behavior of zirconium diboride (ZrB2)-silicon carbide (SiC) particulate composites containing either carbon powder or SCS-9a silicon carbide fibers was evaluated in air. Constant strain rate compression tests have been performed on these materials at room temperature, 1400, and 1550°C. The degradation of the mechanical properties as a result of atmospheric air exposure at high temperatures has also been studied as a function of exposure time. The ZrB2-SiC material shows excellent strength of 3.1±0.2GPa at room temperature and 0.9±0.1GPa at 1400°C when external defects are eliminated by surface finishing. The presence of C is detrimental to the compressive strength of the ZrB2-SiC-C material, as carbon burns out at high temperatures in air. As-fabricated SCS-9a SiC fiber reinforced ZrB2-SiC composites contain significant matrix microcracking due to residual thermal stresses, and show poor mechanical properties and oxidation resistance. After exposure to air at high temperatures an external SiO2 layer is formed, beneath which ZrB2 oxidizes to ZrO2. A significant reduction in room temperature strength occurs after 16-24h of exposure to air at 1400°C for the ZrB2-SiC material, while for the ZrB2-SiC-C composition this reduction is observed after less than 16h. The thickness of the oxide layer was measured as a function of exposure time and temperatures and the details of oxidation process has been discussed.The European Office of Aerospace Research and Development, Air Force Office of Scientific Research, Air Force Research Laboratory, FA8655-07-1-308

Fugas

Por razones prácticamente obvias, únicamente se analizan las fugas de agua relativas a la Ciudad de México, las cuales oscilan entre 40% y 60% de la red de suministro público. A medida que los avances tecnológicos permiten la detección de fugas no visibles se ha estimado un gran impacto en el sistema de abastecimiento público (CONAGUA, 2010). En el caso de las fugas perceptibles, los usuarios, las autoridades y medios de comunicación han planificado la problemática hasta un punto tal que podrían incidir en las políticas públicas de inversión y abastecimiento, así como los conflictos entre usuarios y autoridades por la regularización del servicio público de abastecimiento.Por razones prácticamente obvias, únicamente se analizan las fugas de agua relativas a la Ciudad de México, las cuales oscilan entre 40% y 60% de la red de suministro público. A medida que los avances tecnológicos permiten la detección de fugas no visibles se ha estimado un gran impacto en el sistema de abastecimiento público (CONAGUA, 2010). En el caso de las fugas perceptibles, los usuarios, las autoridades y medios de comunicación han planificado la problemática hasta un punto tal que podrían incidir en las políticas públicas de inversión y abastecimiento, así como los conflictos entre usuarios y autoridades por la regularización del servicio público de abastecimiento.Unidad Académica Profesional Chimalhuacá