Results 241 to 250 of about 820,067 (303)

Epidemic dynamics prediction using fractional SIRD and deep learning. [PDF]

Sci Rep
Shafqat R, Abuasbeh K, Trabelsi S, Balti M.   +3 more
europepmc   +1 more source

Image Classification using Deep Learning Framework

, 2019
Dr. Shaik Razia, M. V. Dharaneeswara Reddy, K. Jagan Mohan, D. Sai Teja   +3 more
openalex   +1 more source

Smarter Sensors Through Machine Learning: Historical Insights and Emerging Trends across Sensor Technologies

Advanced Functional Materials, EarlyView.
This review highlights how machine learning (ML) algorithms are employed to enhance sensor performance, focusing on gas and physical sensors such as haptic and strain devices. By addressing current bottlenecks and enabling simultaneous improvement of multiple metrics, these approaches pave the way toward next‐generation, real‐world sensor applications.
Kichul Lee, Osman Gul, Yeongjae Kwon, Jaeseok Jeong, Seokjoo Cho, Jihyeon Ahn, Jehee Yu, Cheolmin Kim, Donho Lee, Hyeonseok Han, Byeongju Lee, Jungrak Choi, Ji‐Hwan Ha, Yongrok Jeong, Kyungnam Kang, Ali Javey, Junseong Ahn, Inkyu Park   +17 more
wiley   +1 more source

Hierarchical Deep Reinforcement Learning for Multi-Objective Integrated Circuit Physical Layout Optimization With Congestion-Aware Reward Shaping

Haijian Zhang, Yao Ge, Xiuyuan Zhao, Jiyuan Wang   +3 more
openalex   +1 more source

CURE: A deep learning framework pre-trained on large-scale patient data for treatment effect estimation [PDF]

Ruoqi Liu, Pin‐Yu Chen, Ping Zhang
openalex   +1 more source

Electron–Matter Interactions During Electron Beam Nanopatterning

Advanced Functional Materials, EarlyView.
This article reviews the electron–matter interactions important to nanopatterning with electron beam lithography (EBL). Electron–matter interactions, including secondary electron generation routes, polymer radiolysis, and electron beam induced charging, are discussed.
Camila Faccini de Lima, Prathiba Thamizhavel, Taylor J. Woehl   +2 more
wiley   +1 more source

Deep Learning Models for Colloidal Nanocrystal Synthesis. [PDF]

ACS Nano
Gu K, Liang Y, Su J, Sun P, Peng J, Miao N, Sun Z, Fu Y, Zhong H, Zhang J.   +9 more
europepmc   +1 more source

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

From In‐Silico Optimized Microfabrication to Experimental Validation: Engineering a Tridimensional Epi‐Intraneural Interface

Advanced Functional Materials, EarlyView.
An epi‐intraneural interface is developed through in silico optimization and a novel tridimensional microfabrication pipeline. The device integrates penetrating and epineural contacts on a flexible substrate. Mechanical, electrochemical, and in vivo testing in rat and pig reveal robust implantation, low‐threshold activation, and site‐dependent ...
Federico Ciotti, Andrea Cimolato, Noemi Gozzi, Pietro Palopoli, Luca Brugnoli, Natalija Katic Secerovic, Rebecca Gallivan, Alexander Shokurov, Carlo Menon, Johannes Weichart, Ignacio Delgado‐Martinez, Weiguo Song, Stavros Zanos, Xavier Navarro, Stanisa Raspopovic   +14 more
wiley   +1 more source