Results 41 to 50 of about 7,130 (165)
Journal of Biophotonics, EarlyView.HyperProbe1.1 enables rapid, label‐free biochemical mapping of freshly resected meningiomas. By quantifying endogenous biomarkers such as cytochrome c oxidase, hemoglobin derivatives, and lipids, the system reveals molecular signatures consistent with tumor grading and generates spatial maps that visualize metabolic and vascular heterogeneity across ...
Pietro Ricci +13 more
wiley +1 more source
Remote Sensing, 2022 Recently, hyperspectral image (HSI) classification has become a hot topic in the geographical images research area. Sufficient samples are required for image classes to properly train classification models.
Hasan A. H. Naji +3 more
doaj +1 more source
Locality and Structure Regularized Low Rank Representation for Hyperspectral Image Classification
, 2019 Hyperspectral image (HSI) classification, which aims to assign an accurate label for hyperspectral pixels, has drawn great interest in recent years. Although low rank representation (LRR) has been used to classify HSI, its ability to segment each class ...
He, Xiange, Li, Xuelong, Wang, Qi
core +1 more source
Mid‐Infrared Integrated Photonics: Material Platforms and Emerging Applications
Laser &Photonics Reviews, EarlyView.Mid‐infrared (MIR) integrated photonics enables advanced chemical and biological sensing through the unique absorption features of molecules in the 2–20 µm range. This review highlights recent material advances such as chalcogenide glasses, silicon, and graphene and explores MIR applications in environmental monitoring, medical diagnostics ...
Muhammad Ali Butt +2 more
wiley +1 more source
Remote Sensing, 2019 Many graph embedding methods are developed for dimensionality reduction (DR) of hyperspectral image (HSI), which only use spectral features to reflect a point-to-point intrinsic relation and ignore complex spatial-spectral structure in HSI.
Hong Huang, Meili Chen, Yule Duan
doaj +1 more source
, 2017 This paper proposes a novel deep learning framework named bidirectional-convolutional long short term memory (Bi-CLSTM) network to automatically learn the spectral-spatial feature from hyperspectral images (HSIs).
Hang, Renlong +3 more
core +2 more sources
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 +5 more
wiley +1 more source
Vision Transformer-Based Ensemble Learning for Hyperspectral Image Classification
Remote Sensing, 2023 Hyperspectral image (HSI) classification, due to its characteristic combination of images and spectra, has important applications in various fields through pixel-level image classification.
Jun Liu, Haoran Guo, Yile He, Huali Li
doaj +1 more source
International Journal of Cosmetic Science, EarlyView.This preliminary study attempted to characterize solar lentigines and post‐inflammatory hyperpigmentation (PIH) observed on Japanese women. Colorimetric features and chromophore concentrations were measured using hyperspectral imaging for each hyperpigmentation type.
Victor Egana +4 more
wiley +1 more source
Journal of Microscopy, EarlyView.Abstract Brain surgery is a widely practised and effective treatment for brain tumours, but accurately identifying and classifying tumour boundaries is crucial to maximise resection and avoid neurological complications. This precision in classification is essential for guiding surgical decisions and subsequent treatment planning.
Neetu Sigger +2 more
wiley +1 more source