Results 71 to 80 of about 17,773 (259)

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

HyperKon: A Self-Supervised Contrastive Network for Hyperspectral Image Analysis

Remote Sensing
The use of a pretrained image classification model (trained on cats and dogs, for example) as a perceptual loss function for hyperspectral super-resolution and pansharpening tasks is surprisingly effective.
Daniel La’ah Ayuba, Jean-Yves Guillemaut, Belen Marti-Cardona, Oscar Mendez   +3 more
doaj   +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

Spatial Cell Death and Oxidative Stress Dynamics in Gas Plasma‐Treated Tumor Tissues

Advanced NanoBiomed Research, EarlyView.
Schematic representation of the four experimental models to study tissue penetration and oxidation. Four tissue models were used. Human pancreatic cancer cells were grown on the chorioallantois membrane of chicken embryos and gas plasma‐treated in ovo, murine colorectal tumor tissue was gas plasma‐exposed ex vivo, murine squamous cell carcinoma cells ...
Anke Schmidt, Shahrzad Rokhsary, Linus Hübner, Lea Miebach, Sander Bekeschus   +4 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

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

Comparative Assessment of Landsat‐8 and SPOT‐7 Satellite Data With Field Spectral Measurements for Estimating Plant Diversity in Sandy Grasslands

Biological Diversity, EarlyView.
We compared Landsat‐8 OLI, SPOT, and hyperspectral data for estimating vascular plant diversity in China's Hunshandak Sandland. SPOT data showed the strongest correlation with alpha diversity, followed by hyperspectral data, with Landsat‐8 performing the weakest.
Ying Ye, Jianxiong Lan, Xiaoyue Zhang, Yu Peng   +3 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

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

Effect of Sequential and Combined Space‐Based Stressors on Perovskite Solar Cell Stability

EcoEnergy, EarlyView.
A correlation between loss in performance and mobile ion concentration has been established by sequential stressing of perovskite solar cells under Low Earth Orbit conditions with exposure to protons, light, and thermal cycling. It is shown that the loss in performance increases when ion concentration increases and vice versa.
Saivineeth Penukula, Brandon K. Durant, Megh N. Khanal, Mohin Sharma, Todd A. Byers, Vincent R. Whiteside, Haley P. Harblin, Ian R. Sellers, Bibhudutta Rout, Nicholas Rolston   +9 more
wiley   +1 more source