Results 191 to 200 of about 3,605,315 (303)
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj +4 more
wiley +1 more source
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
Geometrical aspects of lattice gauge equivariant convolutional neural networks
Lattice gauge equivariant convolutional neural networks (L-CNNs) are a framework for convolutional neural networks that can be applied to non-abelian lattice gauge theories without violating gauge symmetry.
Müller, David I., +2 more
core
Selector integration enables scalable memristor crossbar arrays by suppressing sneak‐path currents and improving array selectivity. This review summarizes integration strategies, device requirements, challenges, and opportunities for high‐density memory, compute‐in‐memory, and neuromorphic computing systems.
Zohreh Hajiabadi +3 more
wiley +1 more source
Artificial intelligence in lumbar radiography: bridging deep learning and clinical practice in low-resource environments. [PDF]
Wang YL, Huang S, Lee KC, Cheng CM.
europepmc +1 more source
An oxygen‐controlled iridium‐oxide (IrOx) nano‐net structure is developed to enhance the sensitivity of metal‐electrolyte‐metal‐insulator‐silicon (MEMIS) biosensors. Integrated with a deep learning model, this platform achieves a high accuracy of 94.8% for detecting the breast cancer biomarker LOXL2.
Chiao‐Fan Chiu +9 more
wiley +1 more source
Toward reliable machine learning models for neural circuit inference: A diagnostic study of CNNs on spike trains. [PDF]
Sun X, Lu H, Zeng C, Simha R.
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
A Two-Stage Ensemble Machine Learning Pipeline for Breast Cancer Diagnosis from Digital Mammograms. [PDF]
Martín-Rodríguez F +4 more
europepmc +1 more source

