A survey on generative adversarial networks for imbalance problems in computer vision tasks

Any computer vision application development starts off by acquiring images and data, then preprocessing and pattern recognition steps to perform a task. When the acquired images are highly imbalanced and not adequate, the desired task may not be achievable. Unfortunately, the occurrence of imbalance problems in acquired image datasets in certain complex real-world problems such as anomaly detection, emotion recognition, medical image analysis, fraud detection, metallic surface defect detection, disaster prediction, etc., are inevitable. The performance of computer vision algorithms can significantly deteriorate when the training dataset is imbalanced. In recent years, Generative Adversarial Neural Networks (GANs) have gained immense attention by researchers across a variety of application domains due to their capability to model complex real-world image data. It is particularly important that GANs can not only be used to generate synthetic images, but also its fascinating adversarial learning idea showed good potential in restoring balance in imbalanced datasets. In this paper, we examine the most recent developments of GANs based techniques for addressing imbalance problems in image data. The real-world challenges and implementations of synthetic image generation based on GANs are extensively covered in this survey. Our survey first introduces various imbalance problems in computer vision tasks and its existing solutions, and then examines key concepts such as deep generative image models and GANs. After that, we propose a taxonomy to summarize GANs based techniques for addressing imbalance problems in computer vision tasks into three major categories: 1. Image level imbalances in classification, 2. object level imbalances in object detection and 3. pixel level imbalances in segmentation tasks. We elaborate the imbalance problems of each group, and provide GANs based solutions in each group. Readers will understand how GANs based techniques can handle the problem of imbalances and boost performance of the computer vision algorithms

Intraclass image augmentation for defect detection using generative adversarial neural networks

Surface defect identification based on computer vision algorithms often leads to inadequate generalization ability due to large intraclass variation. Diversity in lighting conditions, noise components, defect size, shape, and position make the problem challenging. To solve the problem, this paper develops a pixel-level image augmentation method that is based on image-to-image translation with generative adversarial neural networks (GANs) conditioned on fine-grained labels. The GAN model proposed in this work, referred to as Magna-Defect-GAN, is capable of taking control of the image generation process and producing image samples that are highly realistic in terms of variations. Firstly, the surface defect dataset based on the magnetic particle inspection (MPI) method is acquired in a controlled environment. Then, the Magna-Defect-GAN model is trained, and new synthetic image samples with large intraclass variations are generated. These synthetic image samples artificially inflate the training dataset size in terms of intraclass diversity. Finally, the enlarged dataset is used to train a defect identification model. Experimental results demonstrate that the Magna-Defect-GAN model can generate realistic and high-resolution surface defect images up to the resolution of 512 × 512 in a controlled manner. We also show that this augmentation method can boost accuracy and be easily adapted to any other surface defect identification models

Influence of the number of players in decision making and performance in the teaching of handball

El balonmano es un deporte en el que se producen numerosas acciones a gran velocidad, en las que la presión del tiempo y el espacio están muy presentes, constituyendo un contexto especial en la toma de decisiones de los jugadores/as. El objetivo principal de la investigación fue estudiar el rendimiento y la toma de decisiones en balonmano usando el Game Perfomance Assessment Instrument (GPAI), en situaciones reducidas de igualdad numérica (tres contra tres) y desigualdad numérica (tres contra dos) durante 396 ciclos de juego realizados por 12 alumnos/as de Bachillerato. Se encontraron diferencias significativas entre las situaciones de igualdad y desigualdad numérica en tres de los siete índices del GPAI: Toma de Decisiones (p=0,047), Ejecución Técnica (p=0,032) y Marcaje (p=0,050). En los dos primeros índices los resultados fueron favorables a las situaciones de desigualdad numérica, mientras que en el tercero los resultados fueron favorables a las situaciones de igualdad numérica. Los resultados permiten constatar que el GPAI puede constituir una herramienta válida de evaluación dentro del contexto educativo ofreciendo una alternativa a la evaluación de modelos orientados exclusivamente hacia la técnica.Handball is a sport in which many actions occur with speed and the pressure of time and space. It constitutes a special context in the decisions making of the players. The aim of this study was to analyze the performance and decision making using the Game Performance Assessment Instrument (GPAI), in situations of numerical equality (three against three) and numerical inequality (three against two) during 396 cycles of game performed by12 students of High School. Significant differences were obtained between the situations of numerical equality and inequality in three of the seven indices: in Decision Making (p=0,047), Technical Execution (p=0,032) and in Mark (p=0,050). In the first two indices the differences were in favor of numerical inequality situations and in the third, the differences were favorable in the situations of numerical equality. Finally, it could be concluded that GPAI is a valid instrument of assessing for an educational context offering an alternative to the evaluation model orientated exclusively towards the skills.peerReviewe

Oral Anticoagulant Adequacy in Non-Valvular Atrial Fibrillation in Primary Care: A Cross-Sectional Study Using Real-World Data (Fantas-TIC Study)

Background: Oral anticoagulants (OAs) are the treatment to prevent stroke in atrial fibrillation (AF). Anticoagulant treatment choice in non-valvular atrial fibrillation (NVAF) must be individualized, taking current guidelines into account. Adequacy of anticoagulant therapy under the current criteria for NVAF in real-world primary care is presented. Methods: Cross-sectional study, with real-world data from patients treated in primary care (PC). Data were obtained from the System for the Improvement of Research in Primary Care (SIDIAP) database, covering 60,978 NVAF-anticoagulated patients from 287 PC centers in 2018. Results: In total, 41,430 (68%) were treated with vitamin K antagonists (VKAs) and 19,548 (32%) NVAF with direct-acting oral anticoagulants (DOACs). Inadequate prescription was estimated to be 36.0% and 67.6%, respectively. Most DOAC inadequacy (77.3%) was due to it being prescribed as a first-line anticoagulant when there was no history of thromboembolic events or intracranial hemorrhage (ICH). A total of 22.1% had missing estimated glomerular filtration rate (eGFR) values. Common causes of inadequate VKA prescription were poor control of time in therapeutic range (TTR) (98.8%) and ICH (2.2%). Conclusions: Poor adequacy to current criteria was observed, being inadequacy higher in DOACs than in VKAs. TTR and GFR should be routinely calculated in electronic health records (EHR) to facilitate decision-making and patient safety

Electrochemical oxidation of meglumine in a pharmaceutical formulation using a nanocomposite anode

The electrocatalytic oxidation of meglumine and gadoterate meglumine (Gd-DOTA) on a TiO2-Ni(SO4)0.3(OH)1.4 composite anode was investigated in alkaline medium (5 M KOH) using cyclic voltammetry and chronoamperometry. The composite was prepared by hydrothermal method and the morphology and structure of the produced nanoparticles were studied by scanning electron microscopy with energy-dispersive X-ray spectroscopy, X-ray diffraction, atomic force microscopy, BET surface area analysis and Fourier transform infrared spectroscopy. The characterization revealed the formation of Ni(SO4)0.3(OH)1.4 nanobelts dispersed on TiO2 nanoaggregates. The composite was coated onto a porous graphite rod, showing good adherence without requiring any binder (according to their anodic and cathodic charges). The supported composite was electrocatalytic, allowing the oxidation of meglumine, either as pure reagent or contained in gadoterate meglumine solutions. Electrochemical methods allowed determining the kinetic parameters, such as the electron transfer coefficient α, the total number of electrons n and the standard heterogeneous rate constant k0 for the reaction of meglumine. The chronoamperometric tests informed about the good stability of the composite anode upon meglumine oxidation at +0.6 V for 10 h. The electrochemical oxidation of meglumine in a commercial pharmaceutical formulation (Dotarem®) was corroborated via ultra-high performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry

Specific Recognition of Influenza A/H1N1/2009 Antibodies in Human Serum: A Simple Virus-Free ELISA Method

Although it has been estimated that pandemic Influenza A H1N1/2009 has infected millions of people from April to October 2009, a more precise figure requires a worldwide large-scale diagnosis of the presence of Influenza A/H1N1/2009 antibodies within the population. Assays typically used to estimate antibody titers (hemagglutination inhibition and microneutralization) would require the use of the virus, which would seriously limit broad implementation.An ELISA method to evaluate the presence and relative concentration of specific Influenza A/H1N1/2009 antibodies in human serum samples is presented. The method is based on the use of a histidine-tagged recombinant fragment of the globular region of the hemagglutinin (HA) of the Influenza A H1N1/2009 virus expressed in E. coli.The ELISA method consistently discerns between Inf A H1N1 infected and non-infected subjects, particularly after the third week of infection/exposure. Since it does not require the use of viral particles, it can be easily and quickly implemented in any basic laboratory. In addition, in a scenario of insufficient vaccine availability, the use of this ELISA could be useful to determine if a person has some level of specific antibodies against the virus and presumably at least partial protection

Clinical and laboratory features of anti-MAG neuropathy without monoclonal gammopathy

Antibodies against myelin-associated glycoprotein (MAG) almost invariably appear in the context of an IgM monoclonal gammopathy associated neuropathy. Very few cases of anti-MAG neuropathy lacking IgM-monoclonal gammopathy have been reported. We investigated the presence of anti-MAG antibodies in 69 patients fulfilling diagnostic criteria for CIDP. Anti-MAG antibodies were tested by ELISA and confirmed by immunohistochemistry. We identified four (5.8%) anti-MAG positive patients without detectable IgM-monoclonal gammopathy. In two of them, IgM-monoclonal gammopathy was detected at 3 and 4-year follow-up coinciding with an increase in anti-MAG antibodies titers. In conclusion, anti-MAG antibody testing should be considered in chronic demyelinating neuropathies, even if IgM-monoclonal gammopathy is not detectable

Aprendre a emprendre en el sector audiovisual. El MOOC com a eina per millorar l’empleabilitat.

Es presenta la posada en marxa d’una acció d’innovació docent, promoguda des de l'ensenyament de Comunicació Audiovisual de la Facultat de Biblioteconomia i Documentació de la UB, i portada a terme pel Grup Consolidat d’Innovació Docent GIDC-CAV. Aquesta té com a objectius generals crear continguts i recursos digitals sobre l’emprenedoria en l'àmbit de la comunicació audiovisual en format MOOC i el desenvolupament i l’aplicació d’eines de seguiment del procés d’avaluació i d’aprenentatge.Programa de Millora i Innovació Docent de la Universitat de Barcelona - Vicerectorat de Política Docen