Results 61 to 70 of about 9,650 (249)

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering

Advanced Intelligent Systems, EarlyView.
Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu, Chenggang Lu, Rui Zhang, Haijun Yan, Yesong Xu   +4 more
wiley   +1 more source

Graph inductive learning method for small sample classification of hyperspectral remote sensing images

European Journal of Remote Sensing, 2020
In recent years, deep learning has drawn increasing attention in the field of hyperspectral remote sensing image classification and has achieved great success.
Xibing Zuo, Xuchu Yu, Bing Liu, Pengqiang Zhang, Xiong Tan, Xiangpo Wei   +5 more
doaj   +1 more source

MambaHSINet: A Dual-Branch Bidirectional State Space Network for Hyperspectral Tree Species Classification

Remote Sensing
Hyperspectral remote sensing provides rich spectral information and has been widely used in fine-grained land-cover classification and forest monitoring.
Xinying Liu, Yanfeng Zhang, Junyang Wu, Tianyu Cai, Yumeng Li, Xinran Wang, Xinwei Li   +6 more
doaj   +1 more source

A Robust Rule-Based Ensemble Framework Using Mean-Shift Segmentation for Hyperspectral Image Classification

Remote Sensing, 2019
This paper assesses the performance of DoTRules—a dictionary of trusted rules—as a supervised rule-based ensemble framework based on the mean-shift segmentation for hyperspectral image classification.
Majid Shadman Roodposhti, Arko Lucieer, Asim Anees, Brett A. Bryan   +3 more
doaj   +1 more source

Classification for hyperspectral imaging [PDF]

, 2014
Hyperspectral Imaging is a method of collecting and processing the information across pre-defined electromagnetic spectrum. These measurements make it possible to derive a continuous spectrum for each pixel of the image. After necessary adjustments these image spectra can be compared with database of reflectance spectra in order to recognise tested ...
Polak, Adam, Marshall, Stephen, Ren, Jinchang, Stothard, David J.M.   +3 more
openaire   +1 more source

Vector Attribute Profiles for Hyperspectral Image Classification [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2016
Morphological attribute profiles are among the most prominent spectral–spatial pixel description methods. They are efficient, effective, and highly customizable multiscale tools based on hierarchical representations of a scalar input image. Their application to multivariate images in general and hyperspectral images in particular has been so far ...
Erchan Aptoula, Mauro Dalla Mura, Sébastien Lefèvre   +2 more
openaire   +4 more sources

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

Tackling cancer stemness with nanotechnology in the era of precision medicine

BMEMat, EarlyView.
Precise customization of nanoparticles (NPs) enables active targeting of cancer stem cells (CSCs), thereby improving drug delivery and therapeutic efficacy. NP‐based probing enhances CSC detection through imaging and liquid biopsy, whereas diverse therapeutic payloads improve therapeutic outcomes.
Shaolei Guo, Shun Yao, Lihui Meng, Chunyuan Chen, Yuechu Lucinda Lu, Rong Lu, Kashif Rafiq Zahid, Umar Raza, Qingzhi Wu, Wenli Chen   +9 more
wiley   +1 more source

Cross-Domain CNN for Hyperspectral Image Classification [PDF]

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