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Real-Time Visual Recognition of Ramp Hand Signals for UAS Ground Operations
Real-Time Visual Recognition of Ramp Hand Signals for UAS Ground Operations
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Real-Time Visual Recognition of Ramp Hand Signals for UAS Ground Operations

de Frutos Carro, Miguel Ángel ; LópezHernández, Fernando Carlos ; Granados, José Javier Rainer

Journal of intelligent & robotic systems, 2023-03, Vol.107 (3), p.44, Article 44 [Periódico revisado por pares]

Dordrecht: Springer Netherlands

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2
Dynamic Telemetry and Deep Neural Networks for Anomaly Detection in 6G Software-Defined Networks
Dynamic Telemetry and Deep Neural Networks for Anomaly Detection in 6G Software-Defined Networks
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Dynamic Telemetry and Deep Neural Networks for Anomaly Detection in 6G Software-Defined Networks

Rzym, Grzegorz ; Masny, Amadeusz ; Chołda, Piotr

Electronics (Basel), 2024-01, Vol.13 (2), p.382 [Periódico revisado por pares]

Basel: MDPI AG

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LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles
LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles
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LVD-NMPC: A learning-based vision dynamics approach to nonlinear model predictive control for autonomous vehicles

Grigorescu, Sorin ; Ginerica, Cosmin ; Zaha, Mihai ; Macesanu, Gigel ; Trasnea, Bogdan

International journal of advanced robotic systems, 2021-05, Vol.18 (3), p.172988142110195 [Periódico revisado por pares]

London, England: SAGE Publications

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4
Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control
Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control
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Deep Learning and Artificial Neural Networks for Spacecraft Dynamics, Navigation and Control

Silvestrini, Stefano ; Lavagna, Michèle

Drones (Basel), 2022-09, Vol.6 (10), p.270 [Periódico revisado por pares]

Basel: MDPI AG

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5
RCNet: road classification convolutional neural networks for intelligent vehicle system
RCNet: road classification convolutional neural networks for intelligent vehicle system
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RCNet: road classification convolutional neural networks for intelligent vehicle system

Dewangan, Deepak Kumar ; Sahu, Satya Prakash

Intelligent service robotics, 2021-04, Vol.14 (2), p.199-214 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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6
ANN-Based Dynamic Prediction of Daily Ground Settlement of Foundation Pit Considering Time-Dependent Influence Factors
ANN-Based Dynamic Prediction of Daily Ground Settlement of Foundation Pit Considering Time-Dependent Influence Factors
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ANN-Based Dynamic Prediction of Daily Ground Settlement of Foundation Pit Considering Time-Dependent Influence Factors

Zhang, Zhenyu ; Xu, Rongqiao ; Wu, Xi ; Wang, Jinchang

Applied sciences, 2022-07, Vol.12 (13), p.6324 [Periódico revisado por pares]

Basel: MDPI AG

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7
A dynamic discarding technique to increase speed and preserve accuracy for YOLOv3
A dynamic discarding technique to increase speed and preserve accuracy for YOLOv3
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A dynamic discarding technique to increase speed and preserve accuracy for YOLOv3

Martinez-Alpiste, Ignacio ; Golcarenarenji, Gelayol ; Wang, Qi ; Alcaraz-Calero, Jose Maria

Neural computing & applications, 2021-08, Vol.33 (16), p.9961-9973 [Periódico revisado por pares]

London: Springer London

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8
Bus Driver Head Position Detection Using Capsule Networks under Dynamic Driving Conditions
Bus Driver Head Position Detection Using Capsule Networks under Dynamic Driving Conditions
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Bus Driver Head Position Detection Using Capsule Networks under Dynamic Driving Conditions

Hollósi, János ; Ballagi, Áron ; Kovács, Gábor ; Fischer, Szabolcs ; Nagy, Viktor

Computers (Basel), 2024-03, Vol.13 (3), p.66 [Periódico revisado por pares]

Basel: MDPI AG

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9
Longitudinal deep truck: Deep longitudinal model with application to sim2real deep reinforcement learning for heavy‐duty truck control in the field
Longitudinal deep truck: Deep longitudinal model with application to sim2real deep reinforcement learning for heavy‐duty truck control in the field
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Longitudinal deep truck: Deep longitudinal model with application to sim2real deep reinforcement learning for heavy‐duty truck control in the field

Albeaik, Saleh ; Wu, Trevor ; Vurimi, Ganeshnikhil ; Chou, Fang‐Chieh ; Lu, Xiao‐Yun ; Bayen, Alexandre M.

Journal of field robotics, 2023-03, Vol.40 (2), p.306-329 [Periódico revisado por pares]

Hoboken: Wiley Subscription Services, Inc

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10
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
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Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data

Han, Liang ; Yang, Guijun ; Dai, Huayang ; Xu, Bo ; Yang, Hao ; Feng, Haikuan ; Li, Zhenhai ; Yang, Xiaodong

Plant methods, 2019-02, Vol.15 (1), p.10-10, Article 10 [Periódico revisado por pares]

England: BioMed Central Ltd

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