Results 171 to 180 of about 118,357 (248)

High‐Resolution Diffusion‐Weighted Imaging With Self‐Gated Self‐Supervised Unrolled Reconstruction

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose High‐resolution diffusion‐weighted imaging (DWI) is clinically demanding. The purpose of this work is to develop an efficient self‐supervised algorithm unrolling technique for submillimeter‐resolution DWI. Methods We developed submillimeter DWI acquisition utilizing multi‐band multi‐shot EPI with diffusion shift encoding.
Zhengguo Tan, Patrick A. Liebig, Annika Hofmann, Frederik B. Laun, Florian Knoll   +4 more
wiley   +1 more source

GraphReco: Probabilistic Structure Recognition for Chemical Molecules

ChemistryOpen, EarlyView.
Molecule structure images are unfriendly for machine understanding, blocking productivity improvements in chemical data mining, drug discovery, and many other fields. We present a rule‐based probabilistic Optical Chemical Structure Recognition model to explain and tackle the ambiguity challenges in graph assembly.
Haidong Wang, Yuncheng Yu, Jyh‐Charn Liu   +2 more
wiley   +1 more source

Advancing Extracellular Vesicle Research: A Review of Systems Biology and Multiomics Perspectives

PROTEOMICS, EarlyView.
ABSTRACT Extracellular vesicles (EVs) are membrane‐bound vesicles secreted by various cell types into the extracellular space and play a role in intercellular communication. Their molecular cargo varies depending on the cell of origin and its functional state.
Gloria Kemunto, Samaneh Ghadami, Kristen Dellinger   +2 more
wiley   +1 more source

Leveraging machine learning and citizen science data to describe flowering phenology across South Africa

PLANTS, PEOPLE, PLANET, EarlyView.
Recent shifts in flowering times are an index of, and a response to, human driven climate change. However, most information on these flowering changes is heavily skewed to the northern hemisphere. This imbalance limits our understanding of how climate change is affecting ecosystems, including the mismatches of flowering times between species, increased
Ross D. Stewart, Nicholas W. Bard, Michelle van der Bank, T. Jonathan Davies   +3 more
wiley   +1 more source

Reduced‐Order Modeling of Energetic Materials Using Physics‐Aware Recurrent Convolutional Neural Networks in a Latent Space (LatentPARC)

Propellants, Explosives, Pyrotechnics, EarlyView.
Physics‐Aware Recurrent Convolutional Neural Networks (PARC) can reliably learn the thermomechanics of energetic materials as a function of morphology. This work introduces LatentPARC, which accelerates PARC by modeling the dynamics in a low‐dimensional latent space.
Zoë J. Gray, Joseph B. Choi, Youngsoo Choi, H. Keo Springer, H. S. Udaykumar, Stephen S. Baek   +5 more
wiley   +1 more source

Using deep learning to assess the toxicological effects of sublethal exposure of a novel green pesticide in a stored‐product beetle

Pest Management Science, EarlyView.
This study employs an AI‐driven multidisciplinary approach to increase our understanding of the toxicological effects of sublethal concentrations of carlina oxide on Prostephanus truncatus. Sublethal exposure to the carlina oxide induced changes in motor patterns and thigmotaxis, highlighting its potential role in integrated pest management strategies.
Anita Casadei, Maria C. Boukouvala, Gianluca Manduca, Nickolas G. Kavallieratos, Filippo Maggi, Marta Ferrati, Eleonora Spinozzi, Cesare Stefanini, Antonio DeSimone, Donato Romano   +9 more
wiley   +1 more source

A CNN Approach for Simultaneous Spatiotemporal Fault Interpretation

Quality and Reliability Engineering International, EarlyView.
ABSTRACT Convolutional Neural Networks (CNNs) have emerged as one of the most effective tools for image analysis. In this study, we propose a custom‐designed CNN architecture to construct a process control scheme based on image data. The product image is partitioned into equal‐sized grids, each comprising three channels: (i) reference image, (ii ...
Hamed Sabahno
wiley   +1 more source

Deep Learning–Driven Surface‐Enhanced Raman Scattering–Lateral Flow Immunoassay With Au Nanostars for High‐Accuracy Respiratory Virus Detection

Rare Metals, EarlyView.
ABSTRACT The high accuracy in surface‐enhanced Raman scattering‐lateral flow immunoassays (SERS–LFIAs) is critical for reliable point‐of‐care testing (POCT) in clinical diagnostics. Conventional approaches are often affected by sampling variability and uneven distribution of immunoprobes, leading to unreliable signal fluctuations.
Shuai Zhao, Yan‐Yan Li, Cheng‐Long Lin, Mei‐Mei Xu, Wei‐Da Zhang, Dan Li, Yu‐Si Peng, Masaki Tanemura, Tian‐Shuo Zhao, Yong Yang   +9 more
wiley   +1 more source

Real‐Time Terrain Traversability Analysis and Mapping for Autonomous Robotics in Dynamic Environments: Fusing Appearance‐ and Geometry‐Based Approaches

Journal of Field Robotics, EarlyView.
ABSTRACT This paper presents advanced methodologies for real‐time terrain analysis and mapping in autonomous robotic systems. The focus is on appearance‐based terrain traversability analysis and geometric‐based terrain traceability analysis. In the appearance‐based approach, an enhanced segmentation model using pixel‐based augmentation and 13 unique ...
Semih Beycimen, Dmitry Ignatyev, Argyrios Zolotas   +2 more
wiley   +1 more source

Development and Preliminary Evaluation of a Machine Vision‐Guided Smart Sprayer Prototype Toward Precision Vegetable Weeding

Journal of Field Robotics, EarlyView.
ABSTRACT Sustainable weed management necessitates herbicide‐reduced, precision weed control. Recent advancements in machine vision and artificial intelligence (AI) for weed recognition and localization have created new opportunities for high‐precision weeding. Although blanket spraying systems are widely used for weed removal, machine vision‐guided, AI‐
Boyang Deng, Yuzhen Lu, Daniel Brainard
wiley   +1 more source