Can you use your firearm while competing in the Florida Python Challenge? Here's what to know before it begins.
Learning a stable yet highly discriminative representation space that can simultaneously recognize known categories and discover novel ones from limited labeled data is fundamental to Generalized ...
Abstract: In this article, we propose a minimum simplex convolutional network (MiSiCNet) for deep hyperspectral unmixing. Unlike all the deep learning-based unmixing methods proposed in the literature ...
TSFitPy is a pipeline designed to determine stellar abundances and atmospheric parameters through the use of Nelder-Mead (simplex algorithm) minimization. It calculates model spectra "on the fly" ...
Population histories are encoded by genomic variation among modern individuals. Population genetic inference methods, all theoretically rooted in probabilistic population models, can recover complex ...
Abstract: In this article, we introduce a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted ...
Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...
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