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Times-series data augmentation and deep learning for construction equipment activity recognition
Automated, real-time, and reliable equipment activity recognition on construction sites can
help to minimize idle time, improve operational efficiency, and reduce emissions. Previous …
help to minimize idle time, improve operational efficiency, and reduce emissions. Previous …
DAGA: Data augmentation with a generation approach for low-resource tagging tasks
B Ding, L Liu, L Bing, C Kruengkrai, TH Nguyen… - ar**_A_Time_Series_Data_Augmentation_of_IMU_Data_for_Construction_Equipment_Activity_Identification/links/5d153b7d299bf1547c8420d2/Time-War**-A-Time-Series-Data-Augmentation-of-IMU-Data-for-Construction-Equipment-Activity-Identification.pdf" data-clk="hl=en&sa=T&oi=gga&ct=gga&cd=4&d=264249991791950277&ei=pQm4Z6DPBqq0ieoP69fV6Q4" data-clk-atid="xbmorPfNqgMJ" target="_blank">[PDF] researchgate.net
[PDF][PDF] Window-war**: A time series data augmentation of IMU data for construction equipment activity identification
Automated, real-time, and reliable equipment activity identification on construction sites can
help to minimize idle times, improve operational efficiencies, and reduce emissions. Many …
help to minimize idle times, improve operational efficiencies, and reduce emissions. Many …
A case study of the augmentation and evaluation of training data for deep learning
J Ding, X Li, X Kang, VN Gudivada - Journal of Data and Information …, 2019 - dl.acm.org
Deep learning has been widely used for extracting values from big data. As many other
machine learning algorithms, deep learning requires significant training data. Experiments …
machine learning algorithms, deep learning requires significant training data. Experiments …
A general domain specific feature transfer framework for hybrid domain adaptation
Heterogeneous domain adaptation needs supplementary information to link up different
domains. However, such supplementary information may not always be available in real …
domains. However, such supplementary information may not always be available in real …
Adversarial discriminative sim-to-real transfer of visuo-motor policies
Various approaches have been proposed to learn visuo-motor policies for real-world robotic
applications. One solution is first learning in simulation then transferring to the real world. In …
applications. One solution is first learning in simulation then transferring to the real world. In …
Modular deep q networks for sim-to-real transfer of visuo-motor policies
While deep learning has had significant successes in computer vision thanks to the
abundance of visual data, collecting sufficiently large real-world datasets for robot learning …
abundance of visual data, collecting sufficiently large real-world datasets for robot learning …
[PDF][PDF] Sim-to-real transfer of visuo-motor policies for reaching in clutter: Domain randomization and adaptation with modular networks
A modular method is proposed to learn and transfer visuo-motor policies from simulation to
the real world in an efficient manner by combining domain randomization and adaptation …
the real world in an efficient manner by combining domain randomization and adaptation …