Learning how to be robust: Deep polynomial regression

Polynomial regression is a recurrent problem with a large number of applications. In computer vision it often appears in motion analysis. Whatever the application, standard methods for regression of polynomial models tend to deliver biased results when the input data is heavily contaminated by outliers. Moreover, the problem is even harder when outliers have strong structure. Departing from problem-tailored heuristics for robust estimation of parametric models, we explore deep convolutional neural networks. Our work aims to find a generic approach for training deep regression models without the explicit need of supervised annotation. We bypass the need for a tailored loss function on the regression parameters by attaching to our model a differentiable hard-wired decoder corresponding to the polynomial operation at hand. We demonstrate the value of our findings by comparing with standard robust regression methods. Furthermore, we demonstrate how to use such models for a real computer vision problem, i.e., video stabilization. The qualitative and quantitative experiments show that neural networks are able to learn robustness for general polynomial regression, with results that well overpass scores of traditional robust estimation methods.Comment: 18 pages, conferenc

Agricultura de terrazas en el cerro Tenismo, Toluca. México

Los campesinos mexicanos practican diversos agroecosistemas tradicionales, caso particular, las terrazas.Los campesinos mexicanos practican diversos agroecosistemas tradicionales, caso particular, las terrazas. Este sistema es uno de los más antiguos en el Valle de Toluca y actualmente se encuentra en proceso de abandono. El objetivo fue caracterizar el sistema de terrazas del cerro Tenismo en Calixtlahuaca, Toluca, México, destacando sus componentes principales: muros de contención, zanja, vegetación, cultivos. A partir de la investigación cualitativa, observación directa y la descripción del agroecosistema, se analizan los componentes de quince terrazas de la ladera media y ladera alta del cerro Tenismo. Los resultados indican que las terrazas de Calixtlahuaca con muro de roca y metepantles (semiterraza), son un sistema importante que contribuye a la conservación de las laderas y de donde se obtienen cultivos de autoconsumo. Se concluye que el manejo que realizan los campesinos por medio de las terrazas (muros, zanjas y vegetación) tiene características agroecológicas que contribuyen a la preservación del ambiente.Universidad Autónoma del Estado de México Colegio de Ciencias Geográficas del Estado de México AC

The catalytic Ornstein-Uhlenbeck process with superprocess catalyst

The main objective of this work is to study a natural class of catalytic Ornstein-Uhlenbeck (O-U) processes with a measure-valued random catalyst, for example, super-Brownian motion. We relate this to the class of affine processes that provides a unified setting in which to view Ornstein-Uhlenbeck processes, superprocesses, and Ornstein-Uhlenbeck processes with superprocess catalyst. We then review some basic properties of super-Brownian motion which we need and introduce the Ornstein-Uhlenbeck process with catalyst given by a superprocess. The main results are the affine characterization of the characteristic functional-Laplace transform of the joint catalytic O-U process and catalyst process and the identification of basic properties of the quenched and annealed versions of these processes.Comment: 23 page

Macropoéticas y Micropoéticas de la representación del cuerpo en la iconósfera contemporánea

This essay retrieves the notion of territoriality to lay out the possibility of the construction of a comparative poetic about the representations of the contemporary body within the panorama of the Visual Arts in Latin America and its devices of production, representation, presentation and circulation.Este ensayo recupera la noción de territorialidad para plantear la posibilidad de construir una poética comparada de las figuraciones y representaciones del cuerpo contemporáneo dentro del panorama de las artes visuales en América Latina y sus dispositivos de producción, representación, presentación y circulación.Este ensaio recupera a noção de territorialidade para propor a possibilidade de construir uma poética comparativa de figurações e representações do corpo contemporâneo dentro do panorama das artes visuais na América Latina e seus dispositivos de produção, representação, apresentação e circulação

How do you sleep? Using off the shelf wrist wearables to estimate sleep quality, sleepiness level, chronotype and sleep regularity indicators

This piece of research is situated in the domain of multi-modal analytics. New commercial off the shelf wearables, such as smartwatches or wristbands, are becoming popular and increasingly used for fitness and wellness in a new trend known as the quantified-self movement. The sensors included in these devices (e.g. accelerometer, heart rate) in conjunction with data analytics algorithms are used to provide information such as steps walked, calories consumed, etc. The main goal of this piece of research is to check if new wearable technologies could be used to estimate sleep indicators in an automatic way. The available medical literature proposes several sleep-related features and methods to calculate them involving direct user observation, interviews or specific medical instrumentation. Off the shelf wearable vendors also provide some sleep indicators, such as the sleep duration, the number of awakes or the time to fall asleep. Taking as a reference the results and methods described in the medical literature and the data available in commercial off the shelf wearables, we propose new sleep indicators offering a greater interpretative value: sleep quality, sleepiness level, chronotype. The results obtained after initial experiments demonstrate the feasibility of this approach to be applied in real contexts. Eventually, we plan to apply these solutions to support educational scenarios related to self-regulated learning and teaching support.Agencia Estatal de Investigación | Ref. TIN2016-80515-RXunta de Galicia | Ref. GRC2013-006Universidade de Vig

Estudios sobre Agricultura y conocimiento tradicional en México

La agricultura es una de las actividades importantes para las comunidades rurales en México. Diversas situaciones impactan directamente a los campesinos y sus sistemas agrícolas. Por ejemplo, los productores con agricultura de temporal, son los menos favorecidos con determinadas políticas internacionales como el Tratado de Libre Comercio (TLC), cuyo potencial productivo se ha reducido a niveles de 1.2 por ciento. En las últimas dos décadas se ha dado fuerte impulso a los cultivos comerciales como hortalizas, frutas y flores ocasionando impactos a los productores rurales (Escalante et al. 2007 y 2008). Los campesinos en México se han enfrentado a diferentes situaciones complejas como los impactos de la modernización del sector agropecuario, los proyectos de desarrollo, la expansión de la industria y las áreas urbanas sobre las rurales y los procesos de mundialización de la economía (González 2007). Ante la situación que atraviesa el sector agrícola, es de vital importancia reconsiderar los sistemas agrícolas tradicionales que practican los campesinos. Los estudio sobre agricultura tradicional mexicana han demostrado la diversidad de sistemas que los campesinos han practicado durante cientos de años. Algunos estudios evidencian la historia del control del agua, la tecnología de riego, el manejo de las plantas, la intensificación del uso del suelo, las formas de organización sociopolítica, el mercado y los tipos de asentamientos humanos (Donkin 1979; Palerm 1980; Palerm y Wolf 1980; Doolittle 2004). Otros estudio más específicos se relacionan con el control de procesos erosivos del suelo, el manejo del suelo, la biodiversidad, el conocimiento ecológico tradicional, las estrategias y manejo de agua de riego y de humedales (González 1992; Maimone et al. 2006; Ocampo y Escobedo 2006; Miranda et al. 2009; Pérez 2014). Por consiguiente, el objetivo de este trabajo es presentar cinco estudios de caso que abordan el estudio de la agricultura y el conocimiento tradicional en México, indicando las diferentes temáticas en cuanto al uso y manejo de la agricultura, los suelos, las plantas y la fauna

Evaluation of commercial-off-the-shelf wrist wearables to estimate stress on students

Wearable commercial-off-the-shelf (COTS) devices have become popular during the last years to monitor sports activities, primarily among young people. These devices include sensors to gather data on physiological signals such as heart rate, skin temperature or galvanic skin response. By applying data analytics techniques to these kinds of signals, it is possible to obtain estimations of higher-level aspects of human behavior. In the literature, there are several works describing the use of physiological data collected using clinical devices to obtain information on sleep patterns or stress. However, it is still an open question whether data captured using COTS wrist wearables is sufficient to characterize the learners' psychological state in educational settings. This paper discusses a protocol to evaluate stress estimation from data obtained using COTS wrist wearables. The protocol is carried out in two phases. The first stage consists of a controlled laboratory experiment, where a mobile app is used to induce different stress levels in a student by means of a relaxing video, a Stroop Color and Word test, a Paced Auditory Serial Addition test, and a hyperventilation test. The second phase is carried out in the classroom, where stress is analyzed while performing several academic activities, namely attending to theoretical lectures, doing exercises and other individual activities, and taking short tests and exams. In both cases, both quantitative data obtained from COTS wrist wearables and qualitative data gathered by means of questionnaires are considered. This protocol involves a simple and consistent method with a stress induction app and questionnaires, requiring a limited participation of support staff.Agencia Estatal de Investigación | Ref. TIN2016-80515-

Incremental Few-Shot Object Detection

Most existing object detection methods rely on the availability of abundant labelled training samples per class and offline model training in a batch mode. These requirements substantially limit their scalability to open-ended accommodation of novel classes with limited labelled training data. We present a study aiming to go beyond these limitations by considering the Incremental Few-Shot Detection (iFSD) problem setting, where new classes must be registered incrementally (without revisiting base classes) and with few examples. To this end we propose OpeN-ended Centre nEt (ONCE), a detector designed for incrementally learning to detect novel class objects with few examples. This is achieved by an elegant adaptation of the CentreNet detector to the few-shot learning scenario, and meta-learning a class-specific code generator model for registering novel classes. ONCE fully respects the incremental learning paradigm, with novel class registration requiring only a single forward pass of few-shot training samples, and no access to base classes -- thus making it suitable for deployment on embedded devices. Extensive experiments conducted on both the standard object detection and fashion landmark detection tasks show the feasibility of iFSD for the first time, opening an interesting and very important line of research.Comment: CVPR 202