Results 71 to 80 of about 2,642,787 (294)
Correlation Hyperspectral Imaging
Hyperspectral imaging aims at providing information on both the spatial and the spectral distribution of light, with high resolution. However, state-of-the-art protocols are characterized by an intrinsic trade-off imposing to sacrifice either resolution or image acquisition speed.
Gianlorenzo Massaro +2 more
openaire +4 more sources
Implementation strategies for hyperspectral unmixing using Bayesian source separation. [PDF]
Positive Source Separation (BPSS) is a useful unsupervised approach for hyperspectral data unmixing, where numerical non-negativity of spectra and abundances has to be ensured, such in remote sensing. Moreover, it is sensible to impose a sum-to-one (full
Moussaoui, Saïd +11 more
core +1 more source
Super‐multiplexed Label‐free Raman Imaging (SLRI) enables 2D/3D metabolic mapping of intact Drosophila testes. Moving beyond descriptive morphology, it establishes a multidimensional tool for tissue metabolic remodeling, and offers a generalizable platform for complex tissue analysis, with implications extending to development and disease. ABSTRACT The
Jiaxin Li +23 more
wiley +1 more source
Multi-channel volume density neural radiance field for hyperspectral imaging
Hyperspectral imaging and Neural Radiance Field (NeRF) can be combined in powerful ways. With limited hyperspectral images, NeRF can generate images of objects with spectral information from arbitrary viewpoints, which can effectively mitigate defects ...
Runchuan Ma, Sailing He
doaj +1 more source
A General Deep Learning Point–Surface Fusion Framework for RGB Image Super-Resolution
Hyperspectral images are usually acquired in a scanning-based way, which can cause inconvenience in some situations. In these cases, RGB image spectral super-resolution technology emerges as an alternative.
Yan Zhang +3 more
doaj +1 more source
Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O. +3 more
core +1 more source
Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li +11 more
wiley +1 more source
CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang +4 more
wiley +1 more source
Quality criteria benchmark for hyperspectral imagery [PDF]
Hyperspectral data appear to be of a growing interest over the past few years. However, applications for hyperspectral data are still in their infancy as handling the significant size of the data presents a challenge for the user community.
Christophe, Emmanuel +2 more
core +1 more source
Enviromics and Abiotic Enviromics: Enhancing Stress Biology and Plant Resilience Breeding
Environmental stressors are captured through high‐throughput envirotyping and integrated into an enviromic framework with genomic, transcriptomic, phenomic, and environmental data. AI/ML models enable prediction and guide marker‐assisted selection, genomic selection, genome editing, and gene pyramiding toward improved abiotic stress tolerance, yield ...
Guangchao Sun +6 more
wiley +1 more source

