368 research outputs found

    Harvesting Training Images for Fine-Grained Object Categories using Visual Descriptions

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    We harvest training images for visual object recognition by casting it as an IR task. In contrast to previous work, we concentrate on fine-grained object categories, such as the large number of particular animal subspecies, for which manual annotation is expensive. We use 'visual descriptions' from nature guides as a novel augmentation to the well-known use of category names. We use these descriptions in both the query process to find potential category images as well as in image reranking where an image is more highly ranked if web page text surrounding it is similar to the visual descriptions. We show the potential of this method when harvesting images for 10 butterfly categories: when compared to a method that relies on the category name only, using visual descriptions improves precision for many categories

    Enhancing Biometric-Capsule-based Authentication and Facial Recognition via Deep Learning

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    In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based authentication systems. Though these systems demonstrate remarkable performance and have seen wide acceptance, they present unique and pressing security and privacy concerns. One proposed method which addresses these concerns is the elegant, fusion-based BioCapsule method. The BioCapsule method is provably secure, privacy-preserving, cancellable and flexible in its secure feature fusion design. In this work, we extend BioCapsule to face-based recognition. Moreover, we incorporate state-of-art deep learning techniques into a BioCapsule-based facial authentication system to further enhance secure recognition accuracy. We compare the performance of an underlying recognition system to the performance of the BioCapsule-embedded system in order to demonstrate the minimal effects of the BioCapsule scheme on underlying system performance. We also demonstrate that the BioCapsule scheme outperforms or performs as well as many other proposed secure biometric techniques

    Fine Scale Nest Site Selection of Greater Sage-Grouse In The Centennial Valley, Montana

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    The purpose of this study was to determine fine scale nest site selection of greater sage-grouse (Centrocercus urophasianus) in the Centennial Valley, MT. A total of ninety nests were found during 2014-2015 using radio-collared sage-grouse. Vegetation surveys were conducted at nests and random sites that measured the nest shrub and the cover available within 3m of the nest. Length of the branch over the nest (Lgth.LB), average axis width of the nest shrub (AvgAxis), lateral cover of the nest shrub (LCShrub), aerial cover of the nest shrub (ACShrub), and height of the lower branch over the nest (Ht.LB) were the habitat variables that received the most support. All habitat variables that were included in the top model were nest shrub morphological characteristics and cover provided by the nest shrub. Therefore, there is strong support that sage-grouse in the Centennial Valley are selecting nest sites based on the morphology of the nest shrub and the cover provided by that nest shrub. None of the habitat variables associated with herbaceous cover received much support for inclusion in our models. On average, residual cover (i.e. grass from previous year) provided concealment for only 4% of the nest bowl. The relative probability of a shrub being selected for a nest site is maximized when Lgth.LB >75cm long, AvgAxis >130cm wide, LCShrub >80%, and ACShrub > 70%. Managers should focus on conserving mountain big sagebrush (Artemisia tridentata ssp. vaseyana) and three-tip sagebrush (Artemisia tripartita) habitats because they were more likely to meet those shrub characteristics

    Fluid Annotation: A Human-Machine Collaboration Interface for Full Image Annotation

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    We introduce Fluid Annotation, an intuitive human-machine collaboration interface for annotating the class label and outline of every object and background region in an image. Fluid annotation is based on three principles: (I) Strong Machine-Learning aid. We start from the output of a strong neural network model, which the annotator can edit by correcting the labels of existing regions, adding new regions to cover missing objects, and removing incorrect regions. The edit operations are also assisted by the model. (II) Full image annotation in a single pass. As opposed to performing a series of small annotation tasks in isolation, we propose a unified interface for full image annotation in a single pass. (III) Empower the annotator. We empower the annotator to choose what to annotate and in which order. This enables concentrating on what the machine does not already know, i.e. putting human effort only on the errors it made. This helps using the annotation budget effectively. Through extensive experiments on the COCO+Stuff dataset, we demonstrate that Fluid Annotation leads to accurate annotations very efficiently, taking three times less annotation time than the popular LabelMe interface.Comment: ACM MultiMedia 2018. Live demo is available at fluidann.appspot.co

    Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

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    Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ Îł, H → Z Z∗ →4l and H →W W∗ →lÎœlÎœ. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined ïŹts probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson

    Standalone vertex ïŹnding in the ATLAS muon spectrometer

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    A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

    Measurement of the top quark-pair production cross section with ATLAS in pp collisions at \sqrt{s}=7\TeV

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    A measurement of the production cross-section for top quark pairs(\ttbar) in pppp collisions at \sqrt{s}=7 \TeV is presented using data recorded with the ATLAS detector at the Large Hadron Collider. Events are selected in two different topologies: single lepton (electron ee or muon Ό\mu) with large missing transverse energy and at least four jets, and dilepton (eeee, ΌΌ\mu\mu or eΌe\mu) with large missing transverse energy and at least two jets. In a data sample of 2.9 pb-1, 37 candidate events are observed in the single-lepton topology and 9 events in the dilepton topology. The corresponding expected backgrounds from non-\ttbar Standard Model processes are estimated using data-driven methods and determined to be 12.2±3.912.2 \pm 3.9 events and 2.5±0.62.5 \pm 0.6 events, respectively. The kinematic properties of the selected events are consistent with SM \ttbar production. The inclusive top quark pair production cross-section is measured to be \sigmattbar=145 \pm 31 ^{+42}_{-27} pb where the first uncertainty is statistical and the second systematic. The measurement agrees with perturbative QCD calculations.Comment: 30 pages plus author list (50 pages total), 9 figures, 11 tables, CERN-PH number and final journal adde

    Measurement of the top quark pair cross section with ATLAS in pp collisions at √s=7 TeV using final states with an electron or a muon and a hadronically decaying τ lepton

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    A measurement of the cross section of top quark pair production in proton-proton collisions recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 7 TeV is reported. The data sample used corresponds to an integrated luminosity of 2.05 fb -1. Events with an isolated electron or muon and a τ lepton decaying hadronically are used. In addition, a large missing transverse momentum and two or more energetic jets are required. At least one of the jets must be identified as originating from a b quark. The measured cross section, σtt-=186±13(stat.)±20(syst.)±7(lumi.) pb, is in good agreement with the Standard Model prediction

    Hunt for new phenomena using large jet multiplicities and missing transverse momentum with ATLAS in 4.7 fb−1 of √s=7 TeV proton-proton collisions

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    Results are presented of a search for new particles decaying to large numbers of jets in association with missing transverse momentum, using 4.7 fb−1 of pp collision data at s√=7TeV collected by the ATLAS experiment at the Large Hadron Collider in 2011. The event selection requires missing transverse momentum, no isolated electrons or muons, and from ≄6 to ≄9 jets. No evidence is found for physics beyond the Standard Model. The results are interpreted in the context of a MSUGRA/CMSSM supersymmetric model, where, for large universal scalar mass m 0, gluino masses smaller than 840 GeV are excluded at the 95% confidence level, extending previously published limits. Within a simplified model containing only a gluino octet and a neutralino, gluino masses smaller than 870 GeV are similarly excluded for neutralino masses below 100 GeV

    Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment

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    This paper describes an analysis of the angular distribution of W->enu and W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with the ATLAS detector at the LHC in 2010, corresponding to an integrated luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and the missing transverse energy, the W decay angular distribution projected onto the transverse plane is obtained and analysed in terms of helicity fractions f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw > 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour, are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017 +/- 0.030, where the first uncertainties are statistical, and the second include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables, revised author list, matches European Journal of Physics C versio
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