Results 91 to 100 of about 4,082 (191)
Harnessing allelic variation to improve the protein content and amino acid profiles of food legumes
Crop Science, Volume 66, Issue 3, May/June 2026.Abstract The growing demand for safe and nutritious foods places unprecedented demands on agriculture. Widespread malnutrition in the Global South could be minimized by including legumes in predominantly cereal‐based cropping systems. Regular legume consumption provides multiple health benefits to humans, positively impacts soil health and microbiome ...
Sangam L. Dwivedi +3 more
wiley +1 more source
Strategies for dimensionality reduction in hyperspectral remote sensing: A comprehensive overview
Egyptian Journal of Remote Sensing and Space SciencesThe technological advancements in spectroscopy give rise to acquiring data about different materials on earth's surface which can be utilized in a variety of potential applications.
Radhesyam Vaddi +4 more
doaj +1 more source
Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics
Advanced Functional Materials, Volume 36, Issue 27, 2 April 2026.Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha +18 more
wiley +1 more source
Spatial–Spectral Split Attention Residual Network for Hyperspectral Image Classification
, 2022 In the past few years, many convolutional neural networks (CNNs) have been applied to hyperspectral image (HSI) classification. However, many of them have the following drawbacks.
Liu, Z +5 more
core +1 more source
Ecohydrology, Volume 19, Issue 3, April/May 2026.ABSTRACT Performing ecohydraulic assessments of salmon habitat is essential for planning and evaluating management actions. Current in situ and modelling approaches, although accurate, can be time‐consuming and expensive, which limits the areal extent of the study.
Jared G. Stieve +2 more
wiley +1 more source
Hyperspectral Image Classification with IFormer Network Feature Extraction
, 2022 Convolutional neural networks (CNNs) are widely used for hyperspectral image (HSI) classification due to their better ability to model the local details of HSI.
Bing Tu, Siyuan Chen, Sha Liao, Qi Ren
core +1 more source
IEEE Access, 2020 Tensor representation is the most natural and effective way to preserve the structural information of hyperspectral image (HSI), and thus is very beneficial to HSI processing.
Lixia Yang +3 more
doaj +1 more source
A Hybrid 3D–2D Feature Hierarchy CNN with Focal Loss for Hyperspectral Image Classification
, 2023 Hyperspectral image (HSI) classification has been extensively applied for analyzing remotely sensed images. HSI data consist of multiple bands that provide abundant spatial information.
Xiaoyan Wen +4 more
core +1 more source
A Bridge Transformer Network With Deep Graph Convolution for Hyperspectral Image Classification
CAAI Transactions on Intelligence Technology, Volume 11, Issue 2, Page 464-482, April 2026.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 +5 more
wiley +1 more source
, 2023 Graph neural networks (GNNs) have a powerful ability to capture long-range spatial correlations in hyperspectral images (HSIs). However, existing GNN-based HSI classification methods are vulnerable to hand-crafted graphs, as the manner in which these ...
Feilong Cao +9 more
core +1 more source