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The ALICE Collaboration at the LHC reports measurement of the inclusive production cross section of electrons from semi-leptonic decays of beauty hadrons with rapidity |y| < 0.8 and transverse momentum 1 < pT < 10 GeV/c, in pp collisions at √s = 2.76 TeV. Electrons not originating from semi-electronic decay of beauty hadrons are suppressed using the impact parameter of the corresponding tracks. The production cross section of beauty decay electrons is compared to the result obtained with an alternative method which uses the distribution of the azimuthal angle between heavy-flavour decay electrons and charged hadrons. Perturbative QCD predictions agree with the measured cross section within the experimental and theoretical uncertainties. The integrated visible cross section, σb→e = 3.47 ± 0.40(stat) +1.12 −1.33(sys) ± 0.07(norm) μb, was extrapolated to full phase space using Fixed Order plus Next-to-Leading Log (FONLL) calculations to obtain the total bb production ¯ cross section, σbb¯ = 130 ± 15.1(stat) +42.1 −49.8(sys) +3.4 −3.1(extr) ± 2.5(norm) ± 4.4(BR) μb.
Efficient algorithms for object recognition are crucial for the newly robotics and computer vision applications that demand real-time and on-line methods. Some examples are autonomous systems, navigating robots, autonomous driving. In this work, we focus on efficient semantic segmentation, which is the problem of labeling each pixel of an image with a semantic class.
Our aim is to speed-up all of the parts of the semantic segmentation pipeline. We also aim at delivering a labeling solution on a time budget, that can be decided on-the-fly. For this purpose, we analyze all the components of the semantic segmentation pipeline, and identify the computational bottleneck of each of them. The different components of the pipeline are over-segmenting the image with local regions, extracting features and classify the local regions, and the final inference of the image labeling with semantic classes. We focus on each of these steps.
First, we introduce a new superpixel algorithm to over-segment the image. Our superpixel method runs in real-time and can deliver a solution at any time budget. Then, for feature extraction, we focus on the framework that computes descriptors and encodes them, followed by a pooling step. We see that the encoding step is the bottleneck, for computational efficiency and performance. We present a novel assignment-based encoding formulation, that allows for the design of a new, very efficient, encoding. Finally, the image labeling output is obtained modeling the dependencies with a Conditional Random Field (CRF). In semantic image segmentation, the computational cost of instantiating the potentials is much higher than MAP inference. We introduce Active MAP inference to on-the-fly select a subset of potentials to be instantiated in the energy function, leaving the rest as unknown, and to estimate the MAP labeling from such incomplete energy function.
We perform experiments on all proposed methods for the different parts of the semantic segmentation pipeline. We show that our superpixel extraction achieves higher accuracy than state-of-the-art on standard superpixel benchmark, while it runs in real-time. We test our feature encoding on standard image classification and segmentation benchmarks, and we show that our method achieves competitive results with the state-of-the-art, and requires less time and memory. Finally, results for semantic segmentation benchmark show that Active MAP inference achieves similar levels of accuracy but with major efficiency gains.
'Provinzielle Weite' ist eine Formulierung, die eine Spannweite aufzumachen gedenkt zwischen einem Verständnis von Provinz/provinziell als beschränkter, statischer, nicht weltoffener Lebens- und Denkweise und einer zwar peripheren Position, die aber gleichwohl gesellschaftliche und mentale Veränderungen sensibel wahrnimmt und künstlerische, technische und wissenschaftliche Innovationen in ihrer ganzen "Weite" zu registrieren und produktiv zu verarbeiten weiß. Im besten Fall kann es sogar geschehen, dass die Provinz die Chance des weit Abgelegenen nutzt, die dort gegebenen Spielräume und Eigenheiten produktiv zu wenden, um damit sogar ins Zentrum zurückzuwirken. Mit dieser Schlusswendung und der Nennung eines Zentrums wird in das Begriffsfeld "provinzielle Weite" eingestandenermaßen eine Denkfigur eingeführt, die mit dem Begriffspaar Peripherie und Zentrum umschrieben ist. Der [...] Abschnitt wird sich allein auf Kerner in Weinsberg konzentrieren, um das erstaunliche Phänomen zu erörtern, auf welche Weise es Justinus Kerner gelang, mit geschärftem Bewusstsein in der Provinz und weitab von der großen Hauptstadt zu leben und doch eine selten erreichte, weltoffene, internationale Plattform errichten zu können, kurz, wie es Kerner schaffte, die weite Welt in der Provinz Weinsberg zu implantieren.