Results 101 to 110 of about 144,445 (263)

Future direction for the deployment of deep learning artificial intelligence: Vision threatening disease detection in underserved communities during COVID-19. [PDF]

Saudi J Ophthalmol, 2023
Vought R, Vought V, Szirth B, Khouri AS.
europepmc   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Deep Learning in GeoSpatial Artificial Intelligence.

, 2017
{"references": ["GeoAI conference, see: https://udi.ornl.gov/geoai.", "Lin Y, Chiang Y-Y, Pan F, Stripelis D, Ambite JL, Eckel SP, Habre R.(2017); Mining public datasets for modeling intra-", "Li, H., Liu, J., & Zhou, X. (2018). Intelligent Map Reader: A Framework for Topographic Map Understanding With Deep Learning and Gazetteer.
openaire   +1 more source

Understanding Operando Water Management in Hydroxide‐Exchange‐Membrane Fuel Cells

Advanced Materials Interfaces, EarlyView.
Effective water management is vital for high‐performance hydroxide‐exchange‐membrane fuel cells. Using a custom water‐flux station, this study quantifies how membrane thickness, microporous layers, and operating conditions dictate internal water transport.
Catherine M. Weiss, Shiyi Wang, Brian P. Setzler, Yushan Yan, Adam Z. Weber   +4 more
wiley   +1 more source

Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine

Advanced Materials Interfaces, EarlyView.
Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee, Mohammad Rabiee, Mohammad Akrami‐Hasan‐Kohal, Sidi A. Bencherif   +3 more
wiley   +1 more source

Generative AI (Artificial Intelligence): What Is It? & What Are Its Inter- And Transdisciplinary Applications? [PDF]

Journal of Systemics, Cybernetics and Informatics
Generative AI can generate new contents in many types of outputs: images, videos, text or music. ChatGPT is web application that uses Generative AI. Many industries such as financial, health care, manufacturing, and marketing and sales use Generative AI.
Richard S. Segall
doaj  

An overview of artificial intelligence/deep learning [PDF]

Pathology, 2021
Jack Garland, Mindy Hu, Kilak Kesha, Charley Glenn, Michael Duffy, Paul Morrow, Simon Stables, Benjamin Ondruschka, Ugo Da Broi, Rexson Tse   +9 more
openaire   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Automatic recognition of teeth and periodontal bone loss measurement in digital radiographs using deep-learning artificial intelligence. [PDF]

J Dent Sci, 2023
Chen CC, Wu YF, Aung LM, Lin JC, Ngo ST, Su JN, Lin YM, Chang WJ.   +7 more
europepmc   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source