Results 61 to 70 of about 1,806,074 (180)

Clustering Hyperspectral Imagery via Sparse Representation Features of the Generalized Orthogonal Matching Pursuit

Remote Sensing
This study focused on improving the clustering performance of hyperspectral imaging (HSI) by employing the Generalized Orthogonal Matching Pursuit (GOMP) algorithm for feature extraction.
Wenqi Guo, Xu Xu, Xiaoqiang Xu, Shichen Gao, Zibu Wu   +4 more
doaj   +1 more source

What Are Computer‐Assisted Methods Achieving in Fine‐Needle Aspiration Cytology of the Pancreas? A Systematic Review and Meta‐Analysis

Cytopathology, EarlyView.
This meta‐analysis demonstrates high diagnostic accuracy of computer‐assisted methods in pancreatic EUS‐FNA cytology (AUC 0.92–0.96) and supports an integrated, cytopathologist‐led workflow in which artificial intelligence functions as an adjunct to diagnostic interpretation and on‐site evaluation (ROSE). Created in BioRender. Mohamed Mirzan, A. (2026)
Al‐Amaan Mohamed Mirzan, Roberto Dina
wiley   +1 more source

Deep Tensor Attention Prior Network for Hyperspectral Image Denoising

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Hyperspectral imaging techniques can generate continuous narrowband images with a high spectral resolution. However, owing to environmental disturbances, atmospheric effects, and hardware limitations of hyperspectral imaging sensors, captured ...
Weilin Shen, Junmin Liu, Jinhai Li, Chao Tian   +3 more
doaj   +1 more source

Brain tissue classification in hyperspectral images using multistage diffusion features and transformer

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, Tuan T. Nguyen, Gianluca Tozzi   +2 more
wiley   +1 more source

A comprehensive review of 3D convolutional neural network-based classification techniques of diseased and defective crops using non-UAV-based hyperspectral images

Smart Agricultural Technology, 2023
Hyperspectral imaging (HSI) is a non-destructive and contactless technology that provides valuable information about the structure and composition of an object. It has the ability to capture detailed information about the chemical and physical properties
Nooshin Noshiri, Michael A. Beck, Christopher P. Bidinosti, Christopher J. Henry   +3 more
doaj   +1 more source

Challenges in Hyperspectral Imaging for Autonomous Driving: The HSI-Drive Case

2025 15th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)
The use of hyperspectral imaging (HSI) in autonomous driving (AD), while promising, faces many challenges related to the specifics and requirements of this application domain. On the one hand, non-controlled and variable lighting conditions, the wide depth-of-field ranges, and dynamic scenes with fast-moving objects. On the other hand, the requirements
Koldo Basterretxea, Jon Gutiérrez-Zaballa, Javier Echanobe   +2 more
openaire   +3 more sources

O129 CLASSIFICATION OF BARRETT’S CARCINOMA SPECIMENS BY HYPERSPECTRAL IMAGING (HSI)

Diseases of the Esophagus, 2019
Abstract Aim Hyperspectral imaging (HSI) technology combines imaging with spectroscopy and can be used for the classification of malignant and non-malignant cells. Thereby HSI combined with artificial intelligent algorithms can be used to predict tumor cells in in Barrett’s carcinoma specimens.
Thieme René, Maktabi Marianne, Köhler Hannes, Chalopin Claire, Jansen-Winkeln Boris, Gockel Ines   +5 more
openaire   +1 more source

HSI-IPGAN: Hyperspectral Image Inpainting via Generative Adversarial Network

, 2023
Abstract Due to the instability of the hyperspectral imaging system and the atmospheric interference, hyperspectral images (HSIs) often suffer from losing the image information of areas with different shapes, which significantly degrades the data quality and further limits the effectiveness of methods for subsequent tasks.
Hu Chen, Jia Li, Junjie Zhang, Liangang Zhang, Dan Zeng   +4 more
openaire   +1 more source

Guiding the AI revolution in periodontology and implant dentistry: Concepts, ethics, accountability, and a roadmap for sustainable adoption

Periodontology 2000, EarlyView.
Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali, Negin Soghli, Patricia A. Miguez   +2 more
wiley   +1 more source

Advances in the tea plants phenotyping using hyperspectral imaging technology

Frontiers in Plant Science
Rapid detection of plant phenotypic traits is crucial for plant breeding and cultivation. Traditional measurement methods are carried out by rich-experienced agronomists, which are time-consuming and labor-intensive.
Baidong Luo, Hongwei Sun, Leilei Zhang, Fengnong Chen, Kaihua Wu   +4 more
doaj   +1 more source