In the field of ship image recognition and classification, traditional algorithms lack attention to the differences between the grain of ship images. The differences in the hull structure of different categories of ships are reflected in the coarse-grain, whereas the differences in the ship equipment and superstructures of different ships of the same category are reflected in the fine-grain. To extract the ship features of different scales, the multi-scale paralleling CNN oriented on ships images (SMS-PCNN) model is proposed in this paper.
View Article and Find Full Text PDFHematite is the absorbing mineral component of dust aerosols in the shortwave spectral region. However, dust shortwave absorption related to hematite suffers from significant uncertainties. In this study, we evaluated available hematite complex refractive index data in the literature on determining the dust effective refractive index at wavelengths ranging from 0.
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