Results 71 to 80 of about 1,349 (217)

Robust Hyperspectral Unmixing with Practical Learning-Based Hyperspectral Image Denoising [PDF]

, 2023
The noise corruption problem commonly exists in hyperspectral images (HSIs) and severely affects the accuracy of hyperspectral unmixing algorithms.
Xiaorun Li, Zeyu Cao, Chaoqun Xia, Yiming Fang, Risheng Huang   +4 more
core   +1 more source

Determination of the transection margin during colorectal resection with hyperspectral imaging (HSI)

International Journal of Colorectal Disease, 2019
This study evaluated the use of hyperspectral imaging for the determination of the resection margin during colorectal resections instead of clinical macroscopic assessment.The used hyperspectral camera is able to record light spectra from 500 to 1000 nm and provides information about physiologic parameters of the recorded tissue area intraoperatively ...
Boris Jansen-Winkeln, N. Holfert, H. Köhler, Y. Moulla, J. P. Takoh, S. M. Rabe, M. Mehdorn, M. Barberio, C. Chalopin, T. Neumuth, I. Gockel   +10 more
openaire   +4 more sources

Hyperspectral Remote Sensing Image Synthesis via Superpixel and Energy-Guided Sampling-Based Diffusion Model

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral remote sensing images (HSIs) contain rich spectral information and have been widely used in agricultural monitoring, mineral analysis, and water monitoring.
Shaokai Weng, Hao Wu, Guowu Yuan, Shuanglin Zu   +3 more
doaj   +1 more source

An Efficient Representation-Based Subspace Clustering Framework for Polarized Hyperspectral Images

Remote Sensing, 2019
Recently, representation-based subspace clustering algorithms for hyperspectral images (HSIs) have been developed with the assumption that pixels belonging to the same land-cover class lie in the same subspace. Polarization is regarded to be a complement
Zhengyi Chen, Chunmin Zhang, Tingkui Mu, Tingyu Yan, Zeyu Chen, Yanqiang Wang   +5 more
doaj   +1 more source

Differentiating solar lentigines from post‐inflammatory hyperpigmentation with hyperspectral imaging: A pilot study

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, Carl Blaksley, Ayako Itaya, Mai Edagawa, Alexandre Nicolas   +4 more
wiley   +1 more source

Gravitation-based edge detection for hyperspectral images [PDF]

, 2017
Edge detection is one of the key issues in the field of computer vision and remote sensing image analysis. Although many different edge-detection methods have been proposed for gray-scale, color, and multispectral images, they still face difficulties ...
Peng Wang, Wang, Peng, Sun, G, Sun, Genyun, Ma, Jingsheng, Jingsheng Ma, Yuanzhi Zhang, Aizhu Zhang, Jia, X ; https://orcid.org/, Ren, Jinchang, Zhang, Yuanzhi, Ma, J, Zhang, Y, Ma, Jingsheng; id_orcid, Jinchang Ren, Zhang, A, Ren, J, Genyun Sun, Wang, P, Jia, Xiuping, Zhang, Aizhu, Xiuping Jia   +21 more
core   +1 more source

HYPERSPECTRAL IMAGE KERNEL SPARSE SUBSPACE CLUSTERING WITH SPATIAL MAX POOLING OPERATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016
In this paper, we present a kernel sparse subspace clustering with spatial max pooling operation (KSSC-SMP) algorithm for hyperspectral remote sensing imagery.
H. Zhang, H. Zhang, H. Zhai, W. Liao, L. Cao, L. Zhang, A. Pižurica   +6 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

Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities

The Plant Phenome Journal, Volume 9, Issue 1, December 2026.
Abstract Artificial intelligence (AI), a key driver of the Fourth Industrial Revolution, is being rapidly integrated into plant phenomics to automate sensing, accelerate data analysis, and support decision‐making in phenomic prediction and genomic selection.
Xu Wang, Daeun Choi, Damian Adams, Jaehyun Ahn, Kelly Balmant, Raquel Dias, Carlos D. Messina, Rafael Muñoz‐Carpena, Vance M. Whitaker, Haipeng Yu, Ziwen Yu, Chang Zhao, Changying Li   +12 more
wiley   +1 more source

Combining Multi-Dimensional Convolutional Neural Network (CNN) With Visualization Method for Detection of Aphis gossypii Glover Infection in Cotton Leaves Using Hyperspectral Imaging

Frontiers in Plant Science, 2021
Cotton is a significant economic crop. It is vulnerable to aphids (Aphis gossypii Glovers) during the growth period. Rapid and early detection has become an important means to deal with aphids in cotton. In this study, the visible/near-infrared (Vis/NIR)
Tianying Yan, Tianying Yan, Wei Xu, Wei Xu, Jiao Lin, Long Duan, Long Duan, Pan Gao, Pan Gao, Chu Zhang, Chu Zhang, Chu Zhang, Xin Lv, Xin Lv   +13 more
doaj   +1 more source