Results 91 to 100 of about 91,296 (293)

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 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

Hyperspectral Imaging Techniques in Search of Geologic Hydrogen: A Review

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
New energy sources are crucial for powering next-generation transportation and supplying reliable energy in remote regions. Hydrogen is an attractive energy carrier because its utilization produces only water as a byproduct.
Roozbeh Rajabi, Martin Stuefer, Mengsu Hu, Marwan Wartes, Amber Zandanel, Mark Ivey   +5 more
doaj   +1 more source

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

Advanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed, Denis Abu Sammour, Dirk C. Hoffmann, Philipp Sievers, Tobias Bausbacher, Melissa Hahn, Yasemin Ucal, Iris Mildenberger, Christiane A. Opitz, Stefan Schmidt, Michael Platten, Oliver Wasenmüller, Wolfgang Wick, Andreas von Deimling, Tobias Kessler, Carsten Hopf   +15 more
wiley   +1 more source

Hyperspectral image unmixing using a multiresolution sticky HDP [PDF]

, 2012
This paper is concerned with joint Bayesian endmember extraction and linear unmixing of hyperspectral images using a spatial prior on the abundance vectors.We propose a generative model for hyperspectral images in which the abundances are sampled from a ...
Hero, Alfred O., Dobigeon, Nicolas, Hero, Alfred, Mittelman, Roni   +3 more
core   +1 more source

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

Cross‐Sectoral AI Integration Is Essential to Tackling Food Waste and Food Insecurity: A Roadmap for Developing Resilient Food Systems

Advanced Intelligent Systems, EarlyView.
As food insecurity and global food demands surge, artificial intelligence (AI)‐based technologies offer promising opportunities to reduce food loss and waste. In this perspective, current AI adoption across the food supply chain is assessed using various academic, industry, and policy sources.
Akansha Prasad, Hannah Mann, Lubna Najm, Shadman Khan, Carlos D. M. Filipe, Tohid F. Didar   +5 more
wiley   +1 more source

Mapping Lupinus polyphyllus density and distribution along road verges using unmanned aerial vehicle (UAV)–based remote sensing

Applications in Plant Sciences, EarlyView.
Abstract Premise Road verges function as refuges for semi‐natural species, but they can also facilitate the spread of non‐native plants such as Lupinus polyphyllus. Unmanned aerial vehicle (UAV)–based remote sensing is a promising tool for mapping these species; however, its application in roadside contexts remains limited.
Elin L. Blomqvist, Jan‐Olov Andersson, R. Lutz Eckstein, Jan Haas   +3 more
wiley   +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

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