Results 151 to 160 of about 52,742 (231)

Ultra‐Low Power Consumption and Highly Durability in Sm:HfO2 Thin Film Ferroelectric Memristor for Edge Detection

Advanced Electronic Materials, EarlyView.
ABSTRACT With the continuous development of computer image processing, developing efficient and low‐power computing devices has become a key challenge. Memristors have integrated in‐situ storage and computing capabilities, making them an ideal choice for low‐power image processing computing architectures. However, current memristors are confronted with
Tengyu Li, YongRui Wang, Weifeng Zhang, Jikang Xu, Xiaobing Yan   +4 more
wiley   +1 more source

Automated detection of wrist ganglia in MRI using convolutional neural networks. [PDF]

BMC Musculoskelet Disord
Hämäläinen M, Sormaala M, Kaseva T, Salli E, Savolainen S, Kangasniemi M.   +5 more
europepmc   +1 more source

Analog Weight Update Rule in Ferroelectric Hafnia, Using picoJoule Programming Pulses

Advanced Electronic Materials, EarlyView.
Resistive, ferroelectric synaptic weights based on BEOL‐compatible hafnia/zirconia nanolaminates are fabricated. Lateral downscaling the devices below 10 µm2 enables 20 ns programming with electrical pulses, dissipating ≤ 3 pJ. Experimental results show that final conductance state is set by pulse amplitude, and is largely independent of the initial ...
Alexandre Baigol, Nikhil Garg, Matteo Mazza, Yanming Zhang, Elisa Zaccaria, Wooseok Choi, Bert Jan Offrein, Laura Bégon‐Lours   +7 more
wiley   +1 more source

Optimizing Image Segmentation for Microstructure Analysis of High-Strength Steel: Histogram-Based Recognition of Martensite and Bainite. [PDF]

Materials (Basel)
Hallo F, Jażdżewski T, Bała P, Korpała G, Regulski K.   +4 more
europepmc   +1 more source

On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification

Advanced Electronic Materials, EarlyView.
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky   +4 more
wiley   +1 more source

Sim-to-real domain adaptation based completion level recognition for autonomous micro-drilling in biomedical application. [PDF]

Sci Rep
Zhao E, Perez SAH, Harada K.
europepmc   +1 more source

Chronic Disease Monitoring Using Advanced Compliant Materials for Bioelectronics

Advanced Electronic Materials, EarlyView.
Compliant bioelectronic systems enable continuous monitoring of chronic disease through soft, stretchable materials and tissue‐conformal designs that support stable electrophysiological, mechanical, and biochemical sensing. Integration of diverse sensing modalities with thoughtful material selection, device architectures, and advanced fabrication ...
Han Kim, Mabel Bartlett, Liyang Wang, Karl Bates, Mengdi He, Myungbo Kim, Carmel Majidi, Tzahi Cohen‐Karni   +7 more
wiley   +1 more source

Smart and efficient waste management through wireless IoT-enabled deep learning. [PDF]

Sci Rep
Latha P, Benni NS, Asuti MG, Thamaraiselvi K.   +3 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
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, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

The principles behind equivariant neural networks for physics and chemistry. [PDF]

Proc Natl Acad Sci U S A
Kondor R.
europepmc   +1 more source