Results 51 to 60 of about 264,274 (268)

Recent advances and applications of deep learning methods in materials science

npj Computational Materials, 2022
Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities.
Kamal Choudhary, Brian DeCost, Chi Chen, Anubhav Jain, Francesca Tavazza, Ryan Cohn, Cheol Woo Park, Alok Choudhary, Ankit Agrawal, Simon J. L. Billinge, Elizabeth Holm, Shyue Ping Ong, Chris Wolverton   +12 more
doaj   +1 more source

DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks [PDF]

, 2018
This paper proposes DeepMarks, a novel end-to-end framework for systematic fingerprinting in the context of Deep Learning (DL). Remarkable progress has been made in the area of deep learning.
Chen, Huili, Koushanfar, Farinaz, Rohani, Bita Darvish   +2 more
core   +1 more source

Structure–Transport–Ion Retention Coupling for Enhanced Nonvolatile Artificial Synapses

Advanced Functional Materials, EarlyView.
Nitrogen incorporation into the conjugated backbone of donor–acceptor polymers enables efficient charge transfer and deep ion embedding in organic electrochemical synaptic transistors (OESTs). This molecular‐level design enhances non‐volatile synaptic properties, providing a new strategy for developing high‐performance and reliable neuromorphic devices.
Donghwa Lee, Jinsung Kim, Sein Chung, Junho Sung, Chaeyeon Han, Eunho Lee   +5 more
wiley   +1 more source

Cognitive Deficit of Deep Learning in Numerosity

, 2018
Subitizing, or the sense of small natural numbers, is an innate cognitive function of humans and primates; it responds to visual stimuli prior to the development of any symbolic skills, language or arithmetic.
Shu, Xiao, Wu, Xiaolin, Zhang, Xi
core   +1 more source

DL-Scale: Deep Learning for model upgrading in topology optimization

Procedia Manufacturing, 2020
Abstract Topology optimization is used for defining the optimal arrangement of material within a specific domain with respect to transferring specific loads to predetermined supports in the best possible way. Deep learning techniques have achieved significant results in computer vision [1], natural language processing [1], big-data management [2 ...
Nikos Ath. Kallioras, Nikos D. Lagaros
openaire   +1 more source

Frontier Advances of Emerging High‐Entropy Anodes in Alkali Metal‐Ion Batteries

Advanced Functional Materials, EarlyView.
Recent advances in microscopic morphology control of high‐entropy anode materials for alkali metal‐ion batteries. Abstract With the growing demand for sustainable energy, portable energy storage systems have become increasingly critical. Among them, the development of rechargeable batteries is primarily driven by breakthroughs in electrode materials ...
Liang Du, Kaidi Zhang, Liang Wang, Di Zhao, Mengqing Hu, Mingli Li, Ming Zhou, Zhenzhen Wu, Mengyang Dong, Bo Fu, Porun Liu, Yun Wang, Hongxia Wang, Yuantong Gu, Lei Zhang   +14 more
wiley   +1 more source

A Review on Bayesian Deep Learning in Healthcare: Applications and Challenges

IEEE Access, 2022
In the last decade, Deep Learning (DL) has revolutionized the use of artificial intelligence, and it has been deployed in different fields of healthcare applications such as image processing, natural language processing, and signal processing.
Abdullah A. Abdullah, Masoud M. Hassan, Yaseen T. Mustafa   +2 more
doaj   +1 more source

Advanced Capsule Networks via Context Awareness

, 2019
Capsule Networks (CN) offer new architectures for Deep Learning (DL) community. Though its effectiveness has been demonstrated in MNIST and smallNORB datasets, the networks still face challenges in other datasets for images with distinct contexts.
Phong, Nguyen Huu, Ribeiro, Bernardete
core   +1 more source

Molecularly Engineered Highly Stable Memristors with Ultra‐Low Operational Voltage: Integrating Synthetic DNA with Quasi‐2D Perovskites

Advanced Functional Materials, EarlyView.
Molecularly engineered memristors integrating Ag nanoparticle–embedded synthetic DNA with quasi‐2D halide perovskites enable ultra‐low‐operational voltage, forming‐free resistive switching, and record‐low power density. This synergistic integration of customized DNA and 2D OHP in bio‐hybrid architecture enhances charge transport, reduces variability ...
Kavya S. Keremane, Abhinav Gorthy, Luyao Zheng, Chiranth C Ravi, Haodong Wu, Jiamao Zheng, Neela H. Yennawar, Shashank Priya, Rashmi Jha, Bed Poudel   +9 more
wiley   +1 more source

Learning Fast and Slow: PROPEDEUTICA for Real-time Malware Detection

, 2017
In this paper, we introduce and evaluate PROPEDEUTICA, a novel methodology and framework for efficient and effective real-time malware detection, leveraging the best of conventional machine learning (ML) and deep learning (DL) algorithms. In PROPEDEUTICA,
Chen, Aokun, Gregio, Andre, He, Pan, Li, Xiaolin, Oliveira, Daniela, Sun, Ruimin, Yuan, Xiaoyong, Zhu, Qile   +7 more
core   +1 more source