RPNet: an End-to-End Network for Relative Camera Pose Estimation

This paper addresses the task of relative camera pose estimation from raw image pixels, by means of deep neural networks. The proposed RPNet network takes pairs of images as input and directly infers the relative poses, without the need of camera intrinsic/extrinsic. While state-of-the-art systems based on SIFT + RANSAC, are able to recover the translation vector only up to scale, RPNet is trained to produce the full translation vector, in an end-to-end way. Experimental results on the Cambridge Landmark dataset show very promising results regarding the recovery of the full translation vector. They also show that RPNet produces more accurate and more stable results than traditional approaches, especially for hard images (repetitive textures, textureless images, etc). To the best of our knowledge, RPNet is the first attempt to recover full translation vectors in relative pose estimation

Results of surgical excision of urethral prolapse in symptomatic patients

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139115/1/nau23232.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139115/2/nau23232_am.pd

Deep Discrete Hashing with Self-supervised Pairwise Labels

Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature representation and end-to-end learning framework. However, the most striking successes in deep hashing have mostly involved discriminative models, which require labels. In this paper, we propose a novel unsupervised deep hashing method, named Deep Discrete Hashing (DDH), for large-scale image retrieval and classification. In the proposed framework, we address two main problems: 1) how to directly learn discrete binary codes? 2) how to equip the binary representation with the ability of accurate image retrieval and classification in an unsupervised way? We resolve these problems by introducing an intermediate variable and a loss function steering the learning process, which is based on the neighborhood structure in the original space. Experimental results on standard datasets (CIFAR-10, NUS-WIDE, and Oxford-17) demonstrate that our DDH significantly outperforms existing hashing methods by large margin in terms of~mAP for image retrieval and object recognition. Code is available at \url{https://github.com/htconquer/ddh}

Real-time event detection in field sport videos

This chapter describes a real-time system for event detection in sports broadcasts. The approach presented is applicable to a wide range of field sports. Using two independent event detection approaches that work simultaneously, the system is capable of accurately detecting scores, near misses, and other exciting parts of a game that do not result in a score. The results obtained across a diverse dataset of different field sports are promising, demonstrating over 90% accuracy for a feature-based event detector and 100% accuracy for a scoreboard-based detector detecting only score

Data circulation in health landscapes

This is the final version. Available from Alma DL Journals via the URL in this record. The crossing boundaries intends to open a dialogue between Science and Technology Studies, Social studies of Health and the emerging Data Journalism perspective. It explores major issues at stake in contemporary practices of producing and sharing data, with a focus on the COVID-19 pandemic

Utilization of Landsat-8 data for the estimation of carrot and maize crop water footprint under the arid climate of Saudi Arabia

Understanding the spatial variability of Water Footprint (WF) of crops is essential for the efficient use of the available water resources. Therefore, this study was designed to bridge the gap in knowledge existed in the area of WF in the arid climate of Saudi Arabia by quantifying the remote sensing based blue-WF (WFblue) of maize and carrot crops cultivated during the period from December 2015 to December 2016. Agrometeorological (empirical) estimated WF components, namely, the WFblue, the green-WF (WFgreen) and the grey-WF (WFgrey), were determined at a farm scale in conjunction with the climatic conditions and cropping patterns. On the other hand, the WFBlue was estimated from Landsat-8 data using energy balance and yield models. The empirical approach based WFBlue was used as a reference for the accuracy assessment of the Landsat-8 estimated WFBlue. The empirically estimated WF of silage maize ranged from 3540 m3 t-1 to 4960 m3 t-1. Out of which the WFgreen, the WFblue and the WFgrey composed 0.74%, 83.28% and 15.98%, respectively. For the carrot crop; however, the WF ranged between 2970 m3 t-1 and 5020 m3 t-1. Where, the WFgreen, the WFblue and the WFgrey represented 0.50%, 77.31% and 22.19%, respectively. Using Landsat-8 data, the WFblue was found to vary across the crops from 2552 m3 t-1 (silage maize) to 3010 m3 t-1 (carrot). Results also revealed a highly significant linear relationship between the empirical and the Landsat-8 derived WFBlue (R2 = 0.77, P>F = 0.001). The utility of Landsat-8 data in mapping WF showed reliable seasonal estimates, which can greatly enhance precision management practices of irrigation water

Dimensiones de la Seguridad Humana y sus políticas públicas en México

El objetivo de esta investigación es profundizar en el análisis de las problemáticas conbase en las cuales se desarrolla la sociedad mexicana desde la perspectiva de la seguridadhumana, lo cual se llevó a cabo mediante el uso de métodos aplicables a las fuenteshistóricas, formales, legislativas y reales del Derecho.De inicio, se identificó como problema central de la investigación de manera sui generisa las 7 dimensiones que integran el concepto de seguridad humana propuesto porla Organización de las Naciones Unidad ONU hace poco más de una década, haciendoespecial énfasis en el ámbito de las políticas públicas, consideradas como factor fundamentalpara la protección de la dignidad humana de los habitantes del país.El desarrollo está integrado por una mirada retrospectiva de la seguridad humana,posteriormente se aborda la temática de las políticas públicas al interior del país, en tornoal mismo objeto de estudio, y se analizan los avances en la puesta en vigencia de las normasjurídicas tendientes a salvaguardar la dignidad individual y colectiva en nuestro país.Finalmente se pasa a una etapa de conclusiones propositivas, en las cuales se establecende manera sintética las perspectivas del autor respecto al tema central del artículo,mismas que evidencian el resultado de investigaciones cuantitativas

Dimensiones de la Seguridad Humana y sus políticas públicas en México

El objetivo de esta investigación es profundizar en el análisis de las problemáticas conbase en las cuales se desarrolla la sociedad mexicana desde la perspectiva de la seguridadhumana, lo cual se llevó a cabo mediante el uso de métodos aplicables a las fuenteshistóricas, formales, legislativas y reales del Derecho.De inicio, se identificó como problema central de la investigación de manera sui generisa las 7 dimensiones que integran el concepto de seguridad humana propuesto porla Organización de las Naciones Unidad ONU hace poco más de una década, haciendoespecial énfasis en el ámbito de las políticas públicas, consideradas como factor fundamentalpara la protección de la dignidad humana de los habitantes del país.El desarrollo está integrado por una mirada retrospectiva de la seguridad humana,posteriormente se aborda la temática de las políticas públicas al interior del país, en tornoal mismo objeto de estudio, y se analizan los avances en la puesta en vigencia de las normasjurídicas tendientes a salvaguardar la dignidad individual y colectiva en nuestro país.Finalmente se pasa a una etapa de conclusiones propositivas, en las cuales se establecende manera sintética las perspectivas del autor respecto al tema central del artículo,mismas que evidencian el resultado de investigaciones cuantitativas

Anti-tissue transglutaminase antibodies in inflammatory and degenerative arthropathies

Recent studies identified tissue transglutaminase (tTG) as the antigen eliciting antiendomysial antibodies (EMA) in celiac disease (CD). Anti-tTG antibodies have therefore been proposed as a serological test for CD. Nevertheless, IgA anti-tTG but not EMA have also been found in inflammatory bowel disease patients, suggesting that these antibodies are linked to a tissue lesion rather than to an auto-immune component of CD. To confirm this hypothesis, we evaluated the presence of IgA anti-tTG in patients with inflammatory and degenerative diseases, in whom tissue lesions presented far away from the intestinal mucosa. The study was carried out on the serum and synovial fluid (SF) of 68 patients with rheumatoid arthritis (RA=33), psoriatic arthritis (PsA=26) and osteoarthritis (OA=9). In RA, PsA and OA sera, IgA anti-tTG were positive in 33%, 42% and 11% of patients, respectively. Serum anti-tTG levels were significantly higher in RA (p<0.0001), PsA (p<0.0001) and OA (p<0.02) with respect to healthy controls. SF anti-tTG levels were significantly higher in PsA (p<0.018) than in OA. A good correlation between serum and synovial fluid anti-tTG levels was found in all arthropathies This study suggests that tTG is not the only antigen of EMA and, furthermore , that IgA anti-tTG antibodies represent a general lesion-associated event. Moreover, the significant correlation between serum and synovial fluid anti-tTG levels allow us to hypothesise that these antibodies could be synthesized in the site of arthritic lesions