The applicability of the ac photovoltaic method and photoconductive decay method using microwaves (µ-PCD method) as bulk lifetime measurement methods were studied. Lifetimes measured by these two methods were compared with bulk lifetimes measured by the photoconductive decay method standardized by ASTM:F28-75. Lifetimes measured by the ac photovoltaic method were in good agreement with the bulk lifetimes of less than 3 ms for both n-type and p-type samples. However, lifetimes measured by the µ-PCD method were significantly lower than the bulk lifetimes. It is concluded that the ac photovoltaic method is a reliable noncontact method for the bulk lifetime measurement of the samples with bulk lifetimes less than 3 ms.
This paper presents a semi-supervised domain adaptation (SSDA) method for Synthetic Aperture Radar (SAR) image classification. SAR imagery is important in ground activity monitoring, but its wide application is impeded due to a lack of annotations. SSDA methods transfer class-discriminative knowledge from a fully-labeled source dataset to a scarcelylabeled target dataset. However, conventional methods often train models which overfit to labeled target data and fail on unlabeled data. To overcome this, we propose to additionally adapt intra-class variations. Specifically, a conversion network is trained to learn from source data the image feature variations caused by the change of image capturing angle. Then synthetic data, which represent a generalized target domain distribution, are estimated by applying the conversion to labeled target data. Our method improves the accuracy of the state-of-the-art SSDA approach from 64.28% to 80.40% in three-shot cases on the SAR ground vehicle dataset.
This paper proposes a high dynamic range rendering method which consists of local luminance correction and global luminance correction. The proposed method estimates the change in the global luminance caused by the local luminance correction in advance, and sets an approximate gamma value for each pixel. The local luminance correction and the global luminance correction are combined to reduce the computation cost in the method. Experiments results demonstrated that the proposed method can successfully enhance image quality and its computational cost is reasonable for imaging appliances.
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