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George Toderici Sean M. O’Malley George Passalis Theoharis Theoharis Ioannis A. Kakadiaris 《International Journal of Computer Vision》2010,89(2-3):382-391
While the retrieval of datasets from human subjects based on demographic characteristics such as gender or race is an ability with wide-ranging application, it remains poorly-studied. In contrast, a large body of work exists in the field of biometrics which has a different goal: the recognition of human subjects. Due to this disparity of interest, existing methods for retrieval based on demographic attributes tend to lag behind the more well-studied algorithms designed purely for face matching. The question this raises is whether a face recognition system could be leveraged to solve these other problems and, if so, how effective it could be. In the current work, we explore the limits of such a system for gender and ethnicity identification given (1) a ground truth of demographically-labeled, textureless 3-D models of human faces and (2) a state-of-the-art face-recognition algorithm. Once trained, our system is capable of classifying the gender and ethnicity of any such model of interest. Experiments are conducted on 4007 facial meshes from the benchmark Face Recognition Grand Challenge v2 dataset. 相似文献
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Joseph Bakarji Daniel O’Malley Velimir V. Vesselinov 《Water Resources Management》2017,31(12):3881-3898
Hybrid socio-hydrological modeling has become indispensable for managing water resources in an increasingly unstable ecology caused by human activity. Most work on the subject has been focused on either qualitative socio-political recommendations with an unbounded list of vague factors or complex sociological and hydrological models with many assumptions and specialized usability. In this paper, we propose a simple agent-based socio-hydrological decision modeling framework for coupling dynamics associated with social behavior and groundwater contamination. The study shows that using social health risk, instead of contaminant concentration, as an optimization variable improves water management decisions aimed at maximizing social wellbeing. The social models and computational framework are designed with enough flexibility and simplicity to encourage extensions to more general socio-hydrological dynamics without compromising either computability or complexity for better data-/model-driven environmental management. 相似文献
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The effectiveness of a reading intervention using the whole-word multimedia software ‘Oxford Reading Tree (ORT) for Clicker’ was compared to a reading intervention using traditional ORT Big Books. Developing literacy skills and attitudes towards learning to read were assessed in a group of 17 struggling beginner readers aged 5–6 years. Each child was given each of the two interventions, and the order of intervention was counterbalanced across the group. Each intervention was integrated into the literacy hour over five consecutive days. Measures of written word recognition, written word naming, phonological awareness and attitudes towards computers were taken before and after each intervention. Significant gains in performance were found following both interventions for all of the literacy measures, but significantly greater gains in written word recognition and enjoyment of instruction were found following the Clicker than Big Book intervention. These results suggest that whole-word multimedia software could be a useful classroom aid for supporting early literacy skills in children who are struggling with learning to read. 相似文献
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