Results 11 to 20 of about 290,773 (308)
Compact Cloud Detection with Bidirectional Self-Attention Knowledge Distillation
Remote Sensing, 2020 The deep convolutional neural network has made significant progress in cloud detection. However, the compromise between having a compact model and high accuracy has always been a challenging task in cloud detection for large-scale remote sensing imagery.
Yajie Chai +6 more
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Surface-Potential-Based Compact Modeling of p-GaN Gate HEMTs
Micromachines, 2021 We propose a surface potential (SP)-based compact model of p-GaN gate high electron mobility transistors (HEMTs) which solves the Poisson equation. The model includes all possible charges in the GaN channel layer, including the unintended Mg doping ...
Jie Wang +5 more
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Cotton disease identification method based on pruning
Frontiers in Plant Science, 2022 Deep convolutional neural networks (DCNN) have shown promising performance in plant disease recognition. However, these networks cannot be deployed on resource-limited smart devices due to their vast parameters and computations.
Dongqin Zhu +4 more
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"A necessary supplement" : what the United Nations global compact is and is not [PDF]
, 2009 The United Nations Global Compact is with currently more than 6,000 voluntary participants the world's largest corporate citizenship initiative. This article first analyzes three critical allegations often made against the Compact by looking at the ...
Rasche, Andreas
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IEEE Journal of the Electron Devices Society, 2023 This paper presents a compact model for organic thin-film transistors fabricated in the staggered or coplanar device architecture which includes short-channel effects related to the potential barrier in the channel region, which manifest themselves as ...
Alexander Kloes +7 more
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Reliable Compact Models for the Investigation of Acoustic High-Frequency Effects in MEMS Transducers
Proceedings, 2018 We present a fully coupled multi-energy domain compact model of a MEMS microphone dedicated to the investigation of acoustic high-frequency effects affecting the device behavior.
Gabriele Bosetti +3 more
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IEEE Access, 2020 A non-iterative learning algorithm for artificial neural networks is an alternative to optimize the neural network parameters with extremely fast convergence time.
Syukron Abu Ishaq Alfarozi +3 more
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Compact conversion and cyclostationary noise modelling of pn junction diodes in low-injection - Part II: Discussion [PDF]
, 2004 Starting from the compact conversion and cyclostationary pn diode noise model presented in the companion paper, we present an extensive validation based on comparisons with physics-based numerical simulations.
Bonani, Fabrizio +2 more
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BSIM-CMG compact model for IC CAD: from FinFET to Gate-All-Around FET Technology
Journal of Microelectronic Manufacturing, 2020 We discuss the BSIM-CMG compact model for SPICE simulations of any common multi-gate (CMG) device. This is an industry standard model which has been used extensively for FinFETs IC design and simulation, and has now been extended to accurately model gate-
Avirup Dasgupta, Chenming Hu
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Environmental impact assessment of introducing compact city models by downscaling simulations [PDF]
, 2020 In this study, first, three compact city models with different degrees of compactness for a prefecture in a large metropolitan area of Japan were designed.
Hashizume, Akari +4 more
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