SSANU-Net: Spatial-Spectral Additive Nonlinear Unmixing Net

New Net Models for Spectral Netlist Partitioning

Spectral approaches for partitioning netlists that use the eigenvectors of a matrix derived from a weighted graph model of the netlist(hypergraph) have been attracting considerable atttention. There are several known ways in which a weighted graph could be derived from the netlist. However, the effectiveness of these alternate net models for netlist partitioning has remained unexplored. In this...

New-emerging approach for fabrication of near net shape aluminum matrix composites/nanocomposites: Ultrasonic additive manufacturing

Recently, high-performance lightweight materials with outstanding mechanical properties have opened up their way to some sophisticated industrial applications. As one of these systems, aluminum matrix composites/nanocomposites (AMCs) offer an outstanding combination of relative density, hardness, wear resistance, and mechanical strength. Until now, several additive manufacturing methods have be...

Net Neutrality vs. Net Neutering

An Overview of Nonlinear Spectral Unmixing Methods in the Processing of Hyperspectral Data

The hyperspectral imagery provides images in hundreds of spectral bands within different wavelength regions. This technology has increasingly applied in different fields of earth sciences, such as minerals exploration, environmental monitoring, agriculture, urban science, and planetary remote sensing. However, despite the ability of these data to detect surface features, the measured spectrum i...

Nonlinear Semi-Supervised Hyperspectral Unmixing Via Semantic Spectral Representation

This paper proposes a new hyperspectral unmixing method for nonlinearly mixed hyperspectral data using a semantic representation in a semi-supervised fashion, assuming the availability of a spectral reference library. Existing semisupervised unmixing algorithms select members from an endmember library that are present at each of the pixels; most such methods assume a linear mixing model. Howeve...