Background modeling by shifted tilings of stacked denoising autoencoders

The effective processing of visual data without interruption is currently of supreme importance. For that purpose, the analysis system must adapt to events that may affect the data quality and maintain its performance level over time. A methodology for background modeling and foreground detection, whose main characteristic is its robustness against stationary noise, is presented in the paper. The system is based on a stacked denoising autoencoder which extracts a set of significant features for each patch of several shifted tilings of the video frame. A probabilistic model for each patch is learned. The distinct patches which include a particular pixel are considered for that pixel classification. The experiments show that classical methods existing in the literature experience drastic performance drops when noise is present in the video sequences, whereas the proposed one seems to be slightly affected. This fact corroborates the idea of robustness of our proposal, in addition to its usefulness for the processing and analysis of continuous data during uninterrupted periods of time.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A new self-organizing neural gas model based on Bregman divergences

In this paper, a new self-organizing neural gas model that we call Growing Hierarchical Bregman Neural Gas (GHBNG) has been proposed. Our proposal is based on the Growing Hierarchical Neural Gas (GHNG) in which Bregman divergences are incorporated in order to compute the winning neuron. This model has been applied to anomaly detection in video sequences together with a Faster R-CNN as an object detector module. Experimental results not only confirm the effectiveness of the GHBNG for the detection of anomalous object in video sequences but also its selforganization capabilities.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Vehicle Type Detection by Convolutional Neural Networks

In this work a new vehicle type detection procedure for traffic surveillance videos is proposed. A Convolutional Neural Network is integrated into a vehicle tracking system in order to accomplish this task. Solutions for vehicle overlapping, differing vehicle sizes and poor spatial resolution are presented. The system is tested on well known benchmarks, and multiclass recognition performance results are reported. Our proposal is shown to attain good results over a wide range of difficult situations.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Road pollution estimation using static cameras and neural networks

Este artículo presenta una metodología para estimar la contaminación en carreteras mediante el análisis de secuencias de video de tráfico. El objetivo es aprovechar la gran red de cámaras IP existente en el sistema de carreteras de cualquier estado o país para estimar la contaminación en cada área. Esta propuesta utiliza redes neuronales de aprendizaje profundo para la detección de objetos, y un modelo de estimación de contaminación basado en la frecuencia de vehículos y su velocidad. Los experimentos muestran prometedores resultados que sugieren que el sistema se puede usar en solitario o combinado con los sistemas existentes para medir la contaminación en carreteras.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

miRNA/phasiRNA mediated regulation of plant defense response against P. syringae

Gene silencing is a mechanism of regulation of gene expression where the small RNAs (sRNAs) are key components for giving specificity to the system. In plants, two main types of noncoding small RNA molecules have been found: microRNAs (miRNAs) and small interfering RNAs (siRNAs). DCL proteins acting on large RNA precursors produce the mature forms of sRNAs (20-24nt) that can act as negative regulators of gene expression. In recent years, the role of miRNAs in regulation of gene expression in plant responses against bacterial pathogens is becoming clearer. Comparisons carried out in our lab between expression profiles of different Arabidopsis thaliana mutants affected in gene silencing, and plants challenged with Pseudomonas syringae pathovar tomato DC3000, led us to identify a set of uncharacterized R genes, belonging to the TIR-NBS-LRR gene family, as differentially expressed in these conditions. Through the use of bioinformatics tools, we found a miRNA* of 22 nt putatively responsible for down-regulating expression of these R genes. We have validated this regulation, and have also established that the corresponding pri-miRNA is down-regulated upon PAMPs or bacteria perception. Using GUS reporters, we have characterized the expression pattern of both pri-miRNA and its best target R genes. We demonstrate that plants with altered levels of miRNA* (knockdown or overexpression lines) exhibit altered PTI-associated phenotypes, supporting a role for this miRNA* in the defence response against this bacterial pathogen. Finally, we identify phasiRNAs that arise from the transcript of one of the R target genes in a miRNA*-RDR6-DCL4-dependent manner.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The molecular environment of the pillar-like features in the HII region G46.5-0.2

At the interface of HII regions and molecular gas peculiar structures appear, some of them with pillar-like shapes. Understanding their origin is important for characterizing triggered star formation and the impact of massive stars on the interstellar medium. In order to study the molecular environment and the influence of the radiation on two pillar-like features related to the HII region G46.5-0.2, we performed molecular line observations with the Atacama Submillimeter Telescope Experiment, and spectroscopic optical observations with the Isaac Newton Telescope. From the optical observations we identified the star that is exciting the HII region as a spectral type O4-6. The molecular data allowed us to study the structure of the pillars and a HCO+ cloud lying between them. In this HCO+ cloud, which have not any well defined 12CO counterpart, we found direct evidence of star formation: two molecular outflows and two associated near-IR nebulosities. The outflows axis orientation is perpendicular to the direction of the radiation flow from the HII region. Several Class I sources are also embedded in this HCO+ cloud, showing that it is usual that the YSOs form large associations occupying a cavity bounded by pillars. On the other hand, it was confirmed that the RDI process is not occurring in one of the pillar tips.Comment: Accepted in MNRAS (2017 June 13

Nanostructures liquids based on octanoic acid vesicles to extract PAHs in food

II Encuentro sobre nanociencia y nanotecnología de investigadores y tecnólogos de la Universidad de Córdoba. NANOUC

Background modeling for video sequences by stacked denoising autoencoders

Nowadays, the analysis and extraction of relevant information in visual data flows is of paramount importance. These images sequences can last for hours, which implies that the model must adapt to all kinds of circumstances so that the performance of the system does not decay over time. In this paper we propose a methodology for background modeling and foreground detection, whose main characteristic is its robustness against stationary noise. Thus, stacked denoising autoencoders are applied to generate a set of robust characteristics for each region or patch of the image, which will be the input of a probabilistic model to determine if that region is background or foreground. The evaluation of a set of heterogeneous sequences results in that, although our proposal is similar to the classical methods existing in the literature, the inclusion of noise in these sequences causes drastic performance drops in the competing methods, while in our case the performance stays or falls slightly.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Light propagation through optical media using metric contact geometry

In this work, we show that the orthogonality between rays and fronts of light propagation in a medium is expressed in terms of a suitable metric contact structure of the optical medium without boundaries. Moreover, we show that considering interfaces (modeled as boundaries) orthogonality is no longer fulfilled, leading to optical aberrations and in some cases total internal reflection. We present some illustrative examples of this latter point.Comment: 8 pages, 7 figure

Energy-Efficient Thermal-Aware Scheduling for RT Tasks Using TCPN

This work leverages TCPNs to design an energy-efficient, thermal-aware real-time scheduler for a multiprocessor system that normally runs in a low state energy at maximum system utilization but its capable of increasing the clock frequency to serve aperiodic tasks, optimizing energy, and honoring temporal and thermal constraints. An off-line stage computes the minimum frequency required to run the periodic tasks at maximum CPU utilization, the proportion of each task''s job to be run on each CPU, the maximum clock frequency that keeps temperature under a limit, and the available cycles (slack) with respect to the system with minimum frequency. Then, a Zero-Laxity online scheduler dispatches the periodic tasks according to the offline calculation. Upon the arrival of aperiodic tasks, it increases clock frequency in such a way that all periodic and aperiodic tasks are properly executed. Thermal and temporal requirements are always guaranteed, and energy consumption is minimized