Results 91 to 100 of about 16,805 (257)
An AI‐enabled micromixing framework is developed by integrating cGAN with Bayesian optimization for predictive control of microrobot‐driven flow manipulation. Through this framework, the spatiotemporal evolution of micromixing is learned directly from experimental images, while rapid identification of optimized microrobot actuation strategies is ...
Dineshkumar Loganathan, Chia‐Yuan Chen
wiley +1 more source
FluoAI is a two‐stage, label‐free method for quantifying nanomaterial‐induced cytotoxicity from conventional fluorescence microscopy images. Mask R‐CNN segmentation and DenseNet‐121 classification provide rapid live/dead classification matching human accuracy.
Ugur C. Topkiran +6 more
wiley +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati +3 more
wiley +1 more source
Extracting the shapes of individual tree crowns from high-resolution imagery can play a crucial role in many applications, including precision agriculture.
Maggi Kelly +5 more
doaj +1 more source
Research on Diaphragm Pump Fault Diagnosis Method Based on Res‐DCB‐Net
ABSTRACT Nonstationary pressure pulsation signals of diaphragm pumps contain strong background noise and coupled characteristics. This makes it challenging to extract incipient fault features and to decouple faults with similar physical mechanisms. To address these limitations, this paper proposes a spatiotemporal fault diagnosis model named Res‐DCB ...
Jiahui Wang +7 more
wiley +1 more source
Integrating machine learning, deep learning, and image analysis for seed species classification
Abstract Premise The growing demand for wildflower seeds in ecological restoration requires reliable species identification, yet current market products often contain heterogeneous species. As seed identification is labor‐intensive and requires advanced botanical knowledge, we evaluated multiple segmentation and classification approaches to determine ...
Jonathan Ashworth +6 more
wiley +1 more source
Intelligent Diagnosis of Concrete Defects Based on Improved Mask R-CNN
With the rapid development of artificial intelligence, computer vision techniques have been successfully applied to concrete defect diagnosis in bridge structural health monitoring. To enhance the accuracy of identifying the location and type of concrete
Caiping Huang, Yongkang Zhou, Xin Xie
doaj +1 more source
ABSTRACT The detection of buried or obscured archaeological features remains a central challenge in landscape archaeology, particularly in the irrigated floodplains of Mesopotamia where levees and canals formed the basis of complex agrarian systems. This study presents a deep learning–based approach for the large‐scale, automated detection of ancient ...
Nazarij Buławka +4 more
wiley +1 more source

