7,728 research outputs found

    Automatic Discovery, Association Estimation and Learning of Semantic Attributes for a Thousand Categories

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    Attribute-based recognition models, due to their impressive performance and their ability to generalize well on novel categories, have been widely adopted for many computer vision applications. However, usually both the attribute vocabulary and the class-attribute associations have to be provided manually by domain experts or large number of annotators. This is very costly and not necessarily optimal regarding recognition performance, and most importantly, it limits the applicability of attribute-based models to large scale data sets. To tackle this problem, we propose an end-to-end unsupervised attribute learning approach. We utilize online text corpora to automatically discover a salient and discriminative vocabulary that correlates well with the human concept of semantic attributes. Moreover, we propose a deep convolutional model to optimize class-attribute associations with a linguistic prior that accounts for noise and missing data in text. In a thorough evaluation on ImageNet, we demonstrate that our model is able to efficiently discover and learn semantic attributes at a large scale. Furthermore, we demonstrate that our model outperforms the state-of-the-art in zero-shot learning on three data sets: ImageNet, Animals with Attributes and aPascal/aYahoo. Finally, we enable attribute-based learning on ImageNet and will share the attributes and associations for future research.Comment: Accepted as a conference paper at CVPR 201

    Fibre composite railway sleeper design by using FE approach and optimization techniques

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    This research work aims to develop an optimal design using Finite Element (FE) and Genetic Algorithm (GA) methods to replace the traditional concrete and timber material by a Synthetic Polyurethane fibre glass composite material in railway sleepers. The conventional timber railway sleeper technology is associated with several technical problems related to its durability and ability to resist cutting and abrading action of the bearing plate. The use of pre-stress concrete sleeper in railway industry has many disadvantages related to the concrete material behaviour to resist dynamic stress that may lead to a significant mechanical damage with feasible fissures and cracks. Scientific researchers have recently developed a new composite material such as Glass Fibre Reinforced Polyurethane (GFRP) foam to replace the conventional one. The mechanical properties of these materials are reliable enough to help solving structural problems such as durability, light weight, long life span (50-60 years), less water absorption, provide electric insulation, excellent resistance of fatigue and ability to recycle. This paper suggests appropriate sleeper design to reduce the volume of the material. The design optimization shows that the sleeper length is more sensitive to the loading type than the other parameters

    T-odd Observables in Elastic Scattering, in Deep Inelastic Processes and in Weak Decays

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    We give a unitary description of T-odd effects in various sectors of atomic, nuclear and particle physics, like elastic scattering, deep inelastic processes and weak decays. This we get thanks to a particular transformation, which leads us to defining two T-odd observables. This approach allows to revise in quite a natural way various azimuthal asymmetries and normal polarizations already predicted or even observed in deep inelastic processes and in weak decays. In the latter case, useful suggestions for phenomenological analyses and an interesting result for normal and transverse polarization are derived

    On Credible Coalitional Deviations by Prudent Players

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    In this paper we first explore the predictive power of the solution notion called conservative stable standard of behaviour (CSSB), introduced by Greenberg (1990) in environments with farsighted players (as modelled in Xue (1998)) as intuitively it is quite nice. Unfortunately, we find that CSSB has a number of undesirable properties. Therefore, we introduce a refinement of this which we call conservative stable weak predictor. We explore some existence properties of this new solution.Coalitions; stable behaviour; perfect foresight
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