Results 71 to 80 of about 1,639 (207)

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 sensor-data-based denoising framework for hyperspectral images [PDF]

, 2015
International audienceMany denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording.
Deger, Ferdinand, Mansouri, Alamin, Voisin, Yvon, Hardeberg, Jon Yngve, Pedersen, Marius   +4 more
core   +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

Terrestrial Ecosystem Detection Based on Deep Learning Framework and Satellite Image Geographical Information

Geoscience Data Journal, Volume 13, Issue 3, July 2026.
The proposed deep learning framework integrates ResNet‐50 and LSTM models to detect and classify terrestrial ecosystems from satellite imagery. The workflow begins with image preprocessing using bilateral, guided, and median filters to enhance image quality and preserve edges.
Liang Dong, Fan Lei, Dongliang Huang, Yuye Gong, Jide Wei, Wenjing She   +5 more
wiley   +1 more source

Removal of Mixed Noise in Hyperspectral Images Based on Subspace Representation and Nonlocal Low-Rank Tensor Decomposition

Sensors
Hyperspectral images (HSIs) contain abundant spectral and spatial structural information, but they are inevitably contaminated by a variety of noises during data reception and transmission, leading to image quality degradation and subsequent application ...
Chun He, Youhua Wei, Ke Guo, Hongwei Han
doaj   +1 more source

Bayesian Approach in a Learning-Based Hyperspectral Image Denoising Framework

IEEE Access, 2021
Hyperspectral images (HSI) are corrupted by a combination of Gaussian and impulse noise. Successful denoising of HSI data increases the accuracy of high-level vision operations like classification, target tracking and land-cover problem. On the one hand,
Hazique Aetesam, Suman Kumar Maji, Hussein Yahia   +2 more
doaj   +1 more source

Bioanalytical TERS and Advanced Data Processing Methods

Journal of Raman Spectroscopy, Volume 57, Issue 6, Page 977-994, June 2026.
Tip‐enhanced Raman spectroscopy delivers label‐free, subnanometer vibrational imaging of biological systems. Recent advances in instrumentation, data analysis, and ambient/liquid operation enable surface‐selective mapping of molecular heterogeneity in proteins, nucleic acids, membranes, and viruses, positioning TERS as a powerful platform for nanoscale
Sarika Joshi, Ankit Dodla, Sarthak Saxena, Twinkle Soni, Sumit Saxena, Shobha Shukla, Bayden R. Wood   +6 more
wiley   +1 more source

Assessing Moisture Content of Coolstored Blueberries During Water Loss Scenarios Using Hyperspectral Imaging

New Zealand Journal of Crop and Horticultural Science, Volume 54, Issue 2, June 2026.
Water loss is a key factor affecting the postharvest quality and shelf life of blueberries, and storage conditions (humidity and time) play an important role in regulating water retention capacity of stored berries. This study aims to explore the variation of moisture content (MC) in blueberries under different storage humidity and storage time ...
RunKai Wang, Craig McGill, Eduardo Sandoval, Mo Li   +3 more
wiley   +1 more source

Learning a Model-Based Deep Hyperspectral Denoiser from a Single Noisy Hyperspectral Image

, 2021
Hyperspectral image (HSI) denoising is a crucial preprocessing procedure to improve the quality of HSI. Model-based methods take the degradation model and the structure of underlying clean HSI into account for denoising but require a large number of ...
Shuyin Tao, Jun Zhou, Fu, G, Xiong, F, Yuntao Qian, Zhou, J, Jianfeng Lu, Lu, J, Guanyiman Fu, Tao, S, Fengchao Xiong, Qian, Y   +11 more
core   +1 more source

Hyperspectral Image Denoising Combining Group Sparse and Representative Coefficient Bidirectional Spatial Spectral Total Variation [PDF]

Jisuanji kexue
Hyperspectral image denoising is a fundamental problem in remote sensing field,which is an important step of preprocessing.Denoising method based on total variation of representative coefficients is widely used in hyperspectral image(HSI) denoising ...
SI Weina, YE Jun, JIANG Bin
doaj   +1 more source