Results 41 to 50 of about 95,777 (258)

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

Atari games and Intel processors

, 2017
The asynchronous nature of the state-of-the-art reinforcement learning algorithms such as the Asynchronous Advantage Actor-Critic algorithm, makes them exceptionally suitable for CPU computations.
Adamski, Robert, Grel, Tomasz, Klimek, Maciej, Michalewski, Henryk   +3 more
core   +1 more source

CLinNET: An Interpretable and Uncertainty‐Aware Deep Learning Framework for Multi‐Modal Clinical Genomics

Advanced Science, EarlyView.
Identifying disease‐causing genes in neurocognitive disorders remains challenging due to variants of uncertain significance. CLinNET employs dual‐branch neural networks integrating Reactome pathways and Gene Ontology terms to provide pathway‐level interpretability of genomic alterations.
Ivan Bakhshayeshi, Mohammad Mahdi Hosseini, Ahmadreza Argha, Roxana Zahedi, Nigel H. Lovell, Hamid Alinejad‐Rokny   +5 more
wiley   +1 more source

Analysis of Correlation Between Secondary PM2.5 and Factory Pollution Sources by Using ANN and the Correlation Coefficient

IEEE Access, 2017
Industry 4.0 is gaining more attention from the public, and thus the correlation between factories and nearby environmental pollution sources is a subject worth in-depth research.
Jui-Hung Chang, Chien-Yuan Tseng
doaj   +1 more source

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks

, 2017
We present a framework for specifying, training, evaluating, and deploying machine learning models. Our focus is on simplifying cutting edge machine learning for practitioners in order to bring such technologies into production.
Cheng, Heng-Tze, Haque, Zakaria, Hong, Lichan, Ispir, Mustafa, Mewald, Clemens, Polosukhin, Illia, Roumpos, Georgios, Sculley, D, Smith, Jamie, Soergel, David, Tang, Yuan, Tucker, Philipp, Wicke, Martin, Xia, Cassandra, Xie, Jianwei   +14 more
core   +1 more source

Nanozymes Integrated Biochips Toward Smart Detection System

Advanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen, Wang Zheng, Zhihui Zhang, Shenping Yu, Xinxin Hang, Han Wu, Xiao‐Wei Xiang, Wei Mu, Yanli Jiao, Zaizai Dong, Lingqian Chang   +10 more
wiley   +1 more source

Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation

, 2018
TensorFlow has been the most widely adopted Machine/Deep Learning framework. However, little exists in the literature that provides a thorough understanding of the capabilities which TensorFlow offers for the distributed training of large ML/DL models ...
Awan, Ammar Ahmad, Bedorf, Jeroen, Chu, Ching-Hsiang, Panda, Dhabaleswar K., Subramoni, Hari   +4 more
core   +1 more source

Polarization‐Dependent 3D Holography Generated by Inverse Design Nanoprinting Metasurface

Advanced Science, EarlyView.
A novel polarization‐dependent 3D holography is proposed by introducing polarization as an additional freedom, enabling enhanced depth selectivity and greater control over holographic reconstruction. The efforts perfectly combine the polarization and 3D holography display into ADAM gradient descent algorithm, the application of nanoprinting further ...
Lingxing Xiong, Jintao Gong, Fei Zhang, Wenhao Miao, Qiong He, Dapeng Zhang, Yangjian Cai, Nan Chi   +7 more
wiley   +1 more source

SR4RS: A Tool for Super Resolution of Remote Sensing Images

Journal of Open Research Software, 2022
The SR4RS software includes tools to apply super-resolution methods on remote sensing images. It employs TensorFlow on the deep learning side, and relies on GDAL and the Orfeo ToolBox to deal with geospatial data. The software is written in simple python,
Rémi Cresson
doaj   +1 more source

TensorQuant - A Simulation Toolbox for Deep Neural Network Quantization

, 2017
Recent research implies that training and inference of deep neural networks (DNN) can be computed with low precision numerical representations of the training/test data, weights and gradients without a general loss in accuracy.
Keuper, Janis, Loroch, Dominik Marek, Pfreundt, Franz-Josef, Wehn, Norbert   +3 more
core   +1 more source