UnDIP is a deep learning-based technique for the linear hyperspectral unmixing problem. The proposed method contains two main steps. First, the endmembers are extracted using a geometric endmember ...
Monocular Simultaneous Localization and Mapping (SLAM), Visual Odometry (VO), and Structure from Motion (SFM) are techniques that have emerged recently to address the problem of reconstructing objects ...
ABSTRACT: This paper presents a new dimension reduction strategy for medium and large-scale linear programming problems. The proposed method uses a subset of the original constraints and combines two ...
Computed tomography-tunable diode laser absorption spectroscopy (CT-TDLAS) has been widely used in the diagnosis of the combustion flow field. Several optimized CT reconstruction algorithms such as ...
Although plant proteins are often considered to have less nutritional quality because of their suboptimal amino acid (AA) content, the wide variety of their sources, both conventional and emerging, ...
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 ...
An increasing number of population genomic studies now try to infer complex models of population history using a number of whole-genome sequences sampled from multiple populations. A key technical ...
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