Results 81 to 90 of about 49,483 (287)

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning

Advanced Intelligent Discovery, EarlyView.
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang, Yongqing Zhang, Xinyu Deng, Hyeon Jeong Lee, Delong Zhang   +4 more
wiley   +1 more source

SSATNet: Spectral-spatial attention transformer for hyperspectral corn image classification

Frontiers in Plant Science
Hyperspectral images are rich in spectral and spatial information, providing a detailed and comprehensive description of objects, which makes hyperspectral image analysis technology essential in intelligent agriculture.
Bin Wang, Gongchao Chen, Juan Wen, Linfang Li, Songlin Jin, Yan Li, Ling Zhou, Weidong Zhang   +7 more
doaj   +1 more source

Archaeological Damage Assessment in Conflict Zones: Integrating Satellite Imagery and Ground Surveys in Daraa, Syria

Archaeological Prospection, EarlyView.
ABSTRACT Satellite remote sensing is among the most significant modern methodologies supporting field archaeology. In addition to its efficiency in identifying archaeological sites, remote sensing offers a safe and cost‐effective approach in conflict zones.
Amal Al Kassem, Kristen Hopper, Ismael M. Ibraheem, Andreas Maier, Mohammad Khair Nassrallah, Jürgen Richter   +5 more
wiley   +1 more source

A novel hyperspectral image classification approach based on multiresolution segmentation with a few labeled samples

International Journal of Advanced Robotic Systems, 2017
Hyperspectral remote sensing technology becomes more and more popular in recent years which can be applied to satellite, plane, and flying robots. An important application of hyperspectral remote sensing is the classification of ground objects.
Binge Cui, Xiudan Ma, Faxi Zhao, Yanan Wu   +3 more
doaj   +1 more source

A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

Remote Sensing, 2016
Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and ...
Yi Wang, Yan Zhang, Haiwei Song
doaj   +1 more source

Cross-Domain CNN for Hyperspectral Image Classification [PDF]

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
IGARSS ...
Lee, Hyungtae, Eum, Sungmin, Kwon, Heesung   +2 more
openaire   +2 more sources

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Hyperspectral Imaging Combined With Image Fusion Features and Machine Learning to Discriminate Different Origins, Grades, and Shelf‐Life of Oranges

Food Safety and Health, EarlyView.
This study verified that it is feasible to distinguish oranges of different origins, grades and shelf lives by using hyperspectral technology. It covers spectral, image and graph technologies, as well as machine learning and deep learning models. ABSTRACT This study reports the first application of hyperspectral feature fusion technology combined with ...
Honghui Xiao, Hao Hu, Hanyi Mei, Hao Deng, Yongzhi Zhang, Jing Nie, Hao Wu, Karyne M. Rogers, Yuwei Yuan, Chunlin Li   +9 more
wiley   +1 more source

Bidirectional-Convolutional LSTM Based Spectral-Spatial Feature Learning for Hyperspectral Image Classification

, 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, Liu, Qingshan, Yuan, Xiaotong, Zhou, Feng   +3 more
core   +2 more sources