Results 91 to 100 of about 9,466 (207)
Limited to the low spatial resolution of the hyperspectral imaging sensor, mixed pixels are inevitable in hyperspectral images. Therefore, to obtain the endmembers and corresponding fractions in mixed pixels, hyperspectral unmixing becomes a hot spot in ...
Yang Shao, Jinhui Lan
doaj +1 more source
Hyperspectral EELS image unmixing
Electron Energy Loss Spectroscopy (EELS) performed in a Scanning Transmission Electron Microscope (STEM) provides hyperspectral images characterized by a large number of pixels and energy channels (typically 100 x 100 x 1000) [1].
Altmann, Yoann +5 more
openaire +2 more sources
Abstract Orbital remote sensing observations are a lynchpin of planetary science research. Hyperspectral infrared spectroscopy in particular is key for planetary mineralogical exploration, for example, CRISM for Mars, as this underpins our understanding of the distribution of specific lithologies and the geological process leading to their formation ...
Robert Platt +2 more
wiley +1 more source
TCCU-Net: Transformer and CNN Collaborative Unmixing Network for Hyperspectral Image
In recent years, deep-learning-based hyperspectral unmixing techniques have garnered increasing attention and made significant advancements. However, relying solely on the use of convolutional neural network (CNN) or transformer approaches is ...
Jianfeng Chen +6 more
doaj +1 more source
Global soil quality standards set by the Food and Agriculture Organization (FAO) and World Health Organization (WHO) are adapted nationally, but diverse terminology and threshold values create regulatory inconsistencies. This variability highlights the urgent need for a harmonised international framework to ensure consistent soil quality assessment and
N. L. J. Rintoul‐Hynes +3 more
wiley +1 more source
Efficient Progressive Mamba Model for Hyperspectral Sequence Unmixing
In recent years, deep learning-based hyperspectral unmixing has increasingly incorporated spatial information to improve performance. However, the extent of spatial information introduced involves a complex tradeoff: too little offers limited gains ...
Yang Liu, Shujun Liu, Huajun Wang
doaj +1 more source
Dictionary-based Tensor Canonical Polyadic Decomposition
To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary.
Cohen, Jérémy E., Gillis, Nicolas
core +1 more source
AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley +1 more source
This paper presents the development of a novel multimodal microscopic spectral imaging system that enables spectroscopic and temporal‐spectral imaging into a unified platform for biomedical applications. The uniqueness of the system lies in its ability to operate in both scanning modes: spectral scanning, which acquires hyperspectral image sequences ...
Siddharth Pal +3 more
wiley +1 more source
Spectral unmixing is a significant challenge in hyperspectral image processing. Existing unmixing methods utilize prior knowledge about the abundance distribution to solve the regularization optimization problem, where the difficulty lies in choosing ...
Li Wang +5 more
doaj +1 more source

