Results 171 to 180 of about 25,088 (256)

Deep Learning for Satellite‐Based Forest Disturbance Monitoring: Recent Advances and Challenges

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.
Overview of key research challenges in forest disturbance monitoring, including the detection of disturbances of varying severity, the attribution of disturbance agents, and the development of models capable of generalizing across regions. ABSTRACT Climate change and land use pressures are intensifying forest disturbances in many world regions, as ...
Carolina Natel, Christoph Molnar, Ricardo Dalagnol, Peer Nowack   +3 more
wiley   +1 more source

Emerging Machine Learning Strategies for Digital Processing and Additive Manufacturing of Advanced Ceramics

International Journal of Applied Ceramic Technology, Volume 23, Issue 3, June 2026.
ABSTRACT Machine learning (ML) techniques are increasingly being applied to the development and processing of advanced ceramics, enabling predictive design, formulation optimization, and improved control of manufacturing workflows. This review presents an integrated and application‐oriented analysis of ML approaches in ceramic engineering, with ...
Sioney Teixeira Monteiro, Isaac A. T. Monteiro, J. R. Fernandez‐Gamboa, Yurimiler Leyet Ruiz   +3 more
wiley   +1 more source

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Solar RRL, Volume 10, Issue 10, 27 May 2026.
Operando photoluminescence image sequences acquired during light‐cycling are used to predict open‐circuit‐voltage transients and Grad‐CAM attribution maps with a CNN‐LSTM‐attention model. Compared with Voc‐luminescence reciprocity‐based calculations, the AI model substantially reduces Voc prediction error, especially in the early‐time metastable regime,
Jackson W. Schall, Leidong Xu, Andrew Glaws, Ambarish Nag, Dana B. Kern, Juliette Ugirumurera   +5 more
wiley   +1 more source

Integrating Artificial Intelligence With Droplet‐Based Microfluidics: Advances, Challenges, and Emerging Opportunities

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai, Sukrit Gaira, Rongfeng Wang, Qingtian Zhang, Ming Li, Liao Wu, Diangeng Li, Yi Li, Chengchen Zhang, Jinhong Guo, Shi‐Yang Tang   +10 more
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, Volume 8, Issue 5, May 2026.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Can surgeons trust AI? Perspectives on machine learning in surgery and the importance of eXplainable Artificial Intelligence (XAI). [PDF]

Langenbecks Arch Surg
Brandenburg JM, Müller-Stich BP, Wagner M, van der Schaar M.   +3 more
europepmc   +1 more source

Driving the neural exposome: Latent mobility states from naturalistic GPS data in older adults

Alzheimer's &Dementia, Volume 22, Issue 5, May 2026.
Abstract INTRODUCTION Naturalistic driving provides real‐world behavioral indicators of early cognitive and functional changes. This study integrated naturalistic driving GPS trajectories collected from in‐vehicle sensors with points of interest (POIs) to quantify daily environmental engagement among older adults who were cognitively normal at ...
Kenan Li, Enbal Shacham, Yiqi Zhu, Jean‐Francois Trani, Ganesh M. Babulal   +4 more
wiley   +1 more source

An Intrusion Detection System over the IoT Data Streams Using eXplainable Artificial Intelligence (XAI). [PDF]

Sensors (Basel)
Alabbadi A, Bajaber F.
europepmc   +1 more source

Explainable Artificial Intelligence Through the Lens of Bibliometric Citation Analysis

Applied Stochastic Models in Business and Industry, Volume 42, Issue 3, May/June 2026.
ABSTRACT This study provides a comprehensive bibliometric analysis of the development of Explainable Artificial Intelligence (XAI) research from 1993 to 2024. The objective is to explore key contributors, thematic trends, and the evolution of methodologies within the field.
Mariateresa Russo, Domenico Vistocco
wiley   +1 more source

An Explainable and Carbon‐Aware Stacked Ensemble Model for Phishing and Impersonation Detection in Online Social Networks

Engineering Reports, Volume 8, Issue 5, May 2026.
EcoSecure‐Phish is an explainable, energy‐aware ensemble framework for detecting phishing and impersonation in online social networks. By integrating optimized boosting models with feature selection and sustainability metrics, it achieves high detection accuracy while reducing latency, energy consumption, and carbon impact for scalable, real‐time ...
Romil Rawat, Priyanka Gupta, K. Sakthidasan Sankaran, Vishwas Dixit, Ankita Chourasia, Yagyanath Rimal   +5 more
wiley   +1 more source