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Hydrogenation effects on crystalline and magnetic structure of nanocomposites (FeCoZr)x(Al2O3)100 − x, 38 ≤ x ≤ 63 at.% are studied by 57Fe Mössbauer spectroscopy and magnetometry. Variations of local structure, blocking temperature and mean FeCoZr nanoparticles’ volume are discussed with respect to (i) composition and (ii) two competing processes—H2 incorporation...
Appropriate datasets are required at all stages of object recognition research, including learning visual models of object and scene categories, detecting and localizing instances of these models in images, and evaluating the performance of recognition algorithms. Current datasets are lacking in several respects, and this paper discusses some of the lessons learned from existing efforts, as well as...
The structure of biological molecules plays an important role in many biological processes. The variation of ambient parameters such as pH, temperature or pressure can influence important properties of protein molecules like conformation or stability. By means of the perturbed angular correlation (PAC) technique and atomic force microscopy (AFM) a conformation change of bovine serum albumin (BSA)...
This paper exploits the context of natural dynamic scenes for human action recognition in video. Human actions are frequently constrained by the purpose and the physical properties of scenes and demonstrate high correlation with particular scene classes. For example, eating often happens in a kitchen while running is more common outdoors. The contribution of this paper is three-fold: (a) we automatically...
The aim of this paper is to address recognition of natural human actions in diverse and realistic video settings. This challenging but important subject has mostly been ignored in the past due to several problems one of which is the lack of realistic and annotated video datasets. Our first contribution is to address this limitation and to investigate the use of movie scripts for automatic annotation...
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior knowledge about inter-class relationships into the visual appearance learning. We show how to build and train a semantic hierarchy of discriminative classifiers and how to use it to perform object detection. We evaluate how...
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