Convolutional neural networks (CNNs) have been extensively applied to hyperspectral (HS)
image classification tasks and achieved promising performance. However, for CNN-based …

Hyperspectral image (HSI) usually holds information of land cover classes as a set of many
contiguous narrow spectral wavelength bands. For its efficient thematic mapping or …

Near-infrared (874–1734 nm) hyperspectral imaging (NIR-HSI) technique combined with
chemometric methods was used to trace origins of 1200 Chinese wolfberry samples, which …

Spinach is prone to spoilage in the course of preservation. Spinach leaves stored at different
temperatures for different durations will have varying degrees of freshness. In order to …

Although extreme learning machines (ELM) have been successfully applied for the
classification of hyperspectral images (HSIs), they still suffer from three main drawbacks …

Due to its excellent performance in high-dimensional space, the kernel extreme learning
machine has been widely used in pattern recognition and machine learning fields. In this …

Hyperspectral imaging (HSI) has attracted the formidable interest of the scientific community
and has been applied to an increasing number of real-life applications to automatically …

Although extreme learning machine (ELM) has successfully been applied to a number of
pattern recognition problems, only with the original ELM it can hardly yield high accuracy for …

Classifying every pixel of a hyperspectral image with a certain land-cover type is the
cornerstone of hyperspectral image analysis. In the present study a segmentation-aided …

Construction waste is a serious problem that should be addressed to protect environment
and save resources, some of which have a high recovery value. To efficiently recover …