Results 71 to 80 of about 4,872 (167)

Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery. [PDF]

ISPRS J Photogramm Remote Sens, 2022
Tagliabue G, Boschetti M, Bramati G, Candiani G, Colombo R, Nutini F, Pompilio L, Rivera-Caicedo JP, Rossi M, Rossini M, Verrelst J, Panigada C.   +11 more
europepmc   +1 more source

Potential of Snapshot-Type Hyperspectral Imagery Using Support Vector Classifier for the Classification of Tomatoes Maturity. [PDF]

Sensors (Basel), 2022
Cho BH, Kim YH, Lee KB, Hong YK, Kim KC.
europepmc   +1 more source

A Review of Virtual Dimensionality for Hyperspectral Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018
Virtual dimensionality (VD) is originally defined as the number of spectrally distinct signatures in hyperspectral data. Unfortunately, there is no provided specific definition of what “spectrally distinct signatures” are. As a result, many techniques developed to estimate VD have produced various values for VD with different interpretations.
openaire   +1 more source

Classification of Toona sinensis Young Leaves Using Machine Learning and UAV-Borne Hyperspectral Imagery. [PDF]

Front Plant Sci, 2022
Wu H, Song Z, Niu X, Liu J, Jiang J, Li Y.   +5 more
europepmc   +1 more source

Spectrally Segmented-Enhanced Neural Network for Precise Land Cover Object Classification in Hyperspectral Imagery

Remote Sensing
The paradigm shift brought by deep learning in land cover object classification in hyperspectral images (HSIs) is undeniable, particularly in addressing the intricate 3D cube structure inherent in HSI data. Leveraging convolutional neural networks (CNNs),
Touhid Islam, Rashedul Islam, Palash Uddin, Anwaar Ulhaq   +3 more
doaj   +1 more source

Polysaccharide determination and habitat classification for fresh Dendrobiums with hyperspectral imagery and modified RBFNN. [PDF]

RSC Adv, 2021
Wei Y, Hu W, Wu F, He Y.
europepmc   +1 more source

The synergic approach between machine learning, chemometrics, and NIR hyperspectral imagery for a real-time, reliable, and accurate prediction of mass loss in cement samples. [PDF]

Heliyon, 2023
Diane A, Saffaj T, Ihssane B, Rabie R.
europepmc   +1 more source

Deep potato - The hyperspectral imagery of potato cultivation with reference agronomic measurements dataset: Towards potato physiological features modeling. [PDF]

Data Brief, 2022
Ruszczak B, Boguszewska-Mańkowska D.
europepmc   +1 more source

Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery. [PDF]

Remote Sens (Basel), 2021
Berger K, Hank T, Halabuk A, Rivera-Caicedo JP, Rivera-Caicedo JP, Wocher M, Mojses M, Gerhátová K, Tagliabue G, Dolz MM, Venteo ABP, Verrelst J.   +11 more
europepmc   +1 more source

Improved Multispectral Target Detection Using Target-Specific Spectral Reconstruction

Remote Sensing
Hyperspectral sensors provide high spectral resolution, enabling accurate material discrimination and effective target detection. However, their practical use is constrained by limited spatial resolution and high acquisition costs.
Nicola Acito, Michael Alibani, Marco Diani   +2 more
doaj   +1 more source