Results 81 to 90 of about 41,575 (296)

Deep Neural Network (DNN).

open access: yes, 2018
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

open access: yesProceedings of the AAAI Conference on Artificial Intelligence, 2020
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

open access: yesAdvanced Science, EarlyView.
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]

open access: yesProceedings on Engineering Sciences
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.

open access: yesPLoS ONE, 2023
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

open access: yesAdvanced Science, EarlyView.
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

Highly accelerated knee magnetic resonance imaging using deep neural network (DNN)–based reconstruction: prospective, multi-reader, multi-vendor study

open access: yesScientific Reports, 2023
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

Retinomorphic Visual Processing Enabled by Contact‐Engineered IGZO Optoelectronic Synaptic Memtransistors

open access: yesAdvanced Science, EarlyView.
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

open access: yes, 2023
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

open access: yesAdvanced Science, EarlyView.
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

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