Results 81 to 90 of about 41,575 (296)
This is a graphical representation of a standard feedforward DNN architecture. The DNN is fed with an input vector x of dimension D which is transformed by the hidden layers hj (composed of Nj hidden units) according to an activation function g and the ...
Doroteo T. Toledano (2175334) +2 more
core +1 more source
DNNs as Layers of Cooperating Classifiers
A robust theoretical framework that can describe and predict the generalization ability of DNNs in general circumstances remains elusive. Classical attempts have produced complexity metrics that rely heavily on global measures of compactness and capacity with little investigation into the effects of sub-component collaboration.
Marelie H. Davel +3 more
openaire +3 more sources
Bias‐Tunable Two‐Terminal Organic Photodetector for Intelligent Imaging
A vertically stacked two‐terminal photodetector with a symmetric donor–acceptor–donor trilayer active exhibits reconfigurable photoresponse with bias‐tunable magnitude and polarity, together with sub‐millisecond response speed and a wide tunable output window.
Sangin Hahn +2 more
wiley +1 more source
DESIGN OF SMART TOURISM SYSTEMS TO FORECAST FOREIGN TOURIST ARRIVAL RATE USING DEEP LEARNING TECHNIQUES [PDF]
India's tourism potential is vast, driven by its rich history, diverse ecology, and extensive natural beauty. The country offers various niche tourism experiences, including cruises, adventure, medical, wellness, sports, MICE, eco-tourism, film, rural ...
Ratna Kanth Gudala +3 more
doaj +1 more source
Prediction of concrete strength using response surface function modified depth neural network.
In order to overcome the discreteness of input data and training data in deep neural network (DNN), the multivariable response surface function was used to revise input data and training data in this paper.
Xiaohong Chen, Yueyue Zhang, Pei Ge
doaj +1 more source
Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai +3 more
wiley +1 more source
In this prospective, multi-reader, multi-vendor study, we evaluated the performance of a commercially available deep neural network (DNN)–based MR image reconstruction in enabling accelerated 2D fast spin-echo (FSE) knee imaging. Forty-five subjects were
Joohee Lee +7 more
doaj +1 more source
Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source
RemovalNet: DNN Fingerprint Removal Attacks
With the performance of deep neural networks (DNNs) remarkably improving, DNNs have been widely used in many areas. Consequently, the DNN model has become a valuable asset, and its intellectual property is safeguarded by ownership verification techniques
Huang, Kunzhe +5 more
core
A Review of Failure Modes and Safety Strategies of Lithium‐Ion Batteries from Materials to Systems
A cascade‐aware framework is presented for lithium‐ion battery safety, linking thermal runaway initiation, acceleration, runaway reaction, and propagation with material‐, cell/pack‐, and system‐level interventions. By integrating failure mechanisms, quantitative safety indicators, and staged interception strategies, this review highlights how safer ...
Jin Hyeok Yang +8 more
wiley +1 more source

