Results 111 to 120 of about 49,483 (287)

HyperKon: A Self-Supervised Contrastive Network for Hyperspectral Image Analysis

Remote Sensing
The use of a pretrained image classification model (trained on cats and dogs, for example) as a perceptual loss function for hyperspectral super-resolution and pansharpening tasks is surprisingly effective.
Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez   +3 more
doaj   +1 more source

Using phenology to improve invasive plant detection in fine‐scale hyperspectral drone‐based images

Remote Sensing in Ecology and Conservation, EarlyView.
Using drone‐based hyperspectral images of mixed temperate successional forests collected over a growing season, detection algorithms were produced for three invasive species of interest, which are not only invasive in Virginia but also much of the U.S.: Ailanthus altissima (tree of heaven), Elaeagnus umbellata (autumn olive), and Rhamnus davurica ...
Kelsey S. Huelsman, Howard E. Epstein, Xi Yang, Roderick Walker   +3 more
wiley   +1 more source

A Marker-Based Approach for the Automated Selection of a Single Segmentation from a Hierarchical Set of Image Segmentations [PDF]

The Hierarchical SEGmentation (HSEG) algorithm, which combines region object finding with region object clustering, has given good performances for multi- and hyperspectral image analysis. This technique produces at its output a hierarchical set of image
Benediktsson, J. A., Chanussot, J., Tarabalka, Y., Tilton, J. C.   +3 more
core   +1 more source

Hyperspectral species maps and LiDAR‐based structured population models show future forest fire frequency may compromise forest resilience

Remote Sensing in Ecology and Conservation, EarlyView.
Monitoring forest recovery from disturbances at scale requires tracking tree dynamics, yet traditional ground‐based approaches are resource‐intensive. We present a pipeline to parameterize integral projection models (IPMs) using LiDAR data and hyperspectral‐based species maps to assess post‐fire recovery across large, forested areas at the Caribou ...
Jessica McLean, Tommaso Jucker, Alice Rosen, Sean M. McMahon, Roberto Salguero‐Gómez   +4 more
wiley   +1 more source

Scale dependence in remotely sensed biodiversity: Leveraging continental‐scale imaging spectroscopy from the National Ecological Observatory Network

Remote Sensing in Ecology and Conservation, EarlyView.
Imaging spectroscopy enables large‐scale biodiversity assessment, yet spectral diversity metrics are scale dependent. Across 15 NEON ecosystems, we find that spectral richness increases sub‐linearly from 3600 m2 to 4 km2, whereas spectral divergence shows weak or inconsistent scaling with area, underscoring the importance of scale‐aware interpretation ...
Meghan T. Hayden, Matthew W. Rossi, Laura E. Dee, Kyle Kovach, Cibele H. Amaral, Jacob Nesslage, Madeline Slimp, Rachel S. Meyer, E. Natasha Stavros   +8 more
wiley   +1 more source

SMILE: Extraction‐free submicron‐resolution mapping of lipid chain length and unsaturation by stimulated Raman imaging

VIEW, EarlyView.
In this work, we develop submicron‐resolution mapping of intracellular lipid elements (SMILE) as an extraction‐free vibrational spectroscopic imaging platform based on hyperspectral stimulated Raman scattering microscopy with a spectral analysis pipeline for pixel‐resolved lipid profiling.
Yihui Zhou, Xiangjie Huang, Xingxin Liu, Ling Zhang, Jie Huang, Jing Zhao, Yongqing Zhang, Jin Zhang, Yanqing Gong, Delong Zhang, Hyeon Jeong Lee   +10 more
wiley   +1 more source

A Bridge Transformer Network With Deep Graph Convolution for Hyperspectral Image Classification

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Transformers have been widely applied to hyperspectral image classification, leveraging their self‐attention mechanism for powerful global modelling. However, two key challenges remain as follows: excessive memory and computational costs from calculating correlations between all tokens (especially as image size or spectral bands increase) and ...
Yuquan Gan, Siyu Wu, Chang Su, Nan Xiang, Zhijie Xu, Yushan Pan   +5 more
wiley   +1 more source

MSFFNet: Multiscale Feature Fusion Network for Small Target Detection in Remote Sensing Images

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the advancement of satellite remote sensing technology, object detection based on high‐resolution remote sensing imagery has emerged as a prominent research focus in the field of computer vision. Although numerous algorithms have been developed for remote sensing image object detection, they still suffer from challenges such as low ...
Hui Zong, Chenbin Wang, Hao Wang, Xin Cheng, Shangbing Gao, Yunyang Yan   +5 more
wiley   +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

Facilitating macrosystem biology with organismal‐scale airborne remote sensing: Challenges and opportunities

Functional Ecology, EarlyView.
Read the free Plain Language Summary for this article on the Journal blog. Abstract Emergent ecosystem properties, such as population and trait distributions, biodiversity and energy and water fluxes, occur because of the dynamic interactions of individuals in their environment.
Sarah J. Graves, Ritesh Chowdhry, Meilun Zhou, Ira Harmon, Ben Weinstein, S. K. Morgan Ernest, Alina Zare, Ethan P. White, Stephanie A. Bohlman   +8 more
wiley   +1 more source