Results 41 to 50 of about 9,650 (249)

Identification of an Osteochondral Erosion Process in Gout Driven by Fibrinogen‐Integrin Activation and Local MSU Crystallization

Advanced Science, EarlyView.
Cartilage injury promotes local fibrinogen deposition, which accelerates monosodium urate crystallization and activates integrin‐mediated matrix‐degradation. This self‐amplifying cycle drives gout‐related cartilage erosion. Disrupting fibrinogen deposition or restoring the cartilage barrier could interrupt this vicious cycle.
Hanlin Xu, Simin Bi, Zhechen Liu, Xiaofeng Zhou, Hengwei Qin, Nicola Dalbeth, Minbiao Ji, Yinghui Hua   +7 more
wiley   +1 more source

DMCCT: Dual-Branch Multi-Granularity Convolutional Cross-Substitution Transformer for Hyperspectral Image Classification

Applied Sciences
In the field of hyperspectral image classification, deep learning technology, especially convolutional neural networks, has achieved remarkable progress.
Laiying Fu, Xiaoyong Chen, Yanan Xu, Xiao Li   +3 more
doaj   +1 more source

Masked Graph Convolutional Network for Small Sample Classification of Hyperspectral Images

Remote Sensing, 2023
The deep learning method has achieved great success in hyperspectral image classification, but the lack of labeled training samples still restricts the development and application of deep learning methods.
Wenkai Liu, Bing Liu, Peipei He, Qingfeng Hu, Kuiliang Gao, Hui Li   +5 more
doaj   +1 more source

Super‐Multiplexed Label‐Free Raman Imaging Uncovers Novel Testicular Metabolic Couplings for Residual Body and Spermatogonial Differentiation

Advanced Science, EarlyView.
Super‐multiplexed Label‐free Raman Imaging (SLRI) enables 2D/3D metabolic mapping of intact Drosophila testes. Moving beyond descriptive morphology, it establishes a multidimensional tool for tissue metabolic remodeling, and offers a generalizable platform for complex tissue analysis, with implications extending to development and disease. ABSTRACT The
Jiaxin Li, Xia Chen, Yujuan Qi, Chen Qiao, Qiuru Huang, Dan Zhao, Weiyi Qian, Li Di, Yi Shi, Xiangqi Hu, Yueyue Shao, Kehan Wang, Zhiyu Tang‐Yang, Hanzhi Zang, Yuwen Du, Anran Dong, Jinxiong Feng, Jiayun Chen, Ying Zheng, Xiaofang Tan, Xiaoyu Zhao, Zhonghua Shi, Bo Zheng, Jun Yu   +23 more
wiley   +1 more source

Efficient Hyperspectral Image Classification Using Discrete Cosine Transform on Limited-Resource Systems

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep learning-based hyperspectral image analysis systems is challenging due
Eungjoo Lee, Lei Pan, Zhu Li, Shuvra S. Bhattacharyya   +3 more
doaj   +1 more source

A Sparse Representation-Based Sample Pseudo-Labeling Method for Hyperspectral Image Classification

Remote Sensing, 2020
Hyperspectral image classification methods may not achieve good performance when a limited number of training samples are provided. However, labeling sufficient samples of hyperspectral images to achieve adequate training is quite expensive and difficult.
Binge Cui, Jiandi Cui, Yan Lu, Nannan Guo, Maoguo Gong   +4 more
doaj   +1 more source

An Innovative Intelligent System with Integrated CNN and SVM: Considering Various Crops through Hyperspectral Image Data

ISPRS International Journal of Geo-Information, 2021
Generation of a thematic map is important for scientists and agriculture engineers in analyzing different crops in a given field. Remote sensing data are well-accepted for image classification on a vast area of crop investigation.
Shiuan Wan, Mei-Ling Yeh, Hong-Lin Ma
doaj   +1 more source

Hyperspectral Image Classification [PDF]

, 2012
One objective of hyperspectral data processing is to classify collected imagery into distinct material constituents relevant to particular applications, and produce classification maps that indicate where the constituents are present. Such information products can include land-cover maps for environmental remote sensing, surface mineral maps for ...
openaire   +1 more source

Advancing Fruit Bioimpedance Monitoring With Sustainable, Soft, And Bio‐Based Electrodes Beyond ECG

Advanced Electronic Materials, EarlyView.
Electrical impedance spectroscopy enables non‐destructive fruit quality monitoring, but conventional ECG and needle electrodes compromise signal stability, fruit physiology, and sustainability. This perspective highlights the transition toward soft, biocompatible, and biodegradable electrode interfaces based on natural substrates, bio‐derived ...
Sundus Riaz, Ahmed Rasheed, Angelo Zanella, Almudena Rivadeneyra, Paolo Lugli, Luisa Petti, Pietro Ibba   +6 more
wiley   +1 more source

A Spectral Spatial Attention Fusion with Deformable Convolutional Residual Network for Hyperspectral Image Classification

Remote Sensing, 2021
Convolutional neural networks (CNNs) have exhibited excellent performance in hyperspectral image classification. However, due to the lack of labeled hyperspectral data, it is difficult to achieve high classification accuracy of hyperspectral images with ...
Tianyu Zhang, Cuiping Shi, Diling Liao, Liguo Wang   +3 more
doaj   +1 more source