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Now showing items 31-37 of 37
Hybrid Modeling of Deformable Linear Objects for Their Cooperative Transportation by Teams of Quadrotors
(MDPI, 2022-05-23)
his paper deals with the control of a team of unmanned air vehicles (UAVs), specifically quadrotors, for which their mission is the transportation of a deformable linear object (DLO), i.e., a cable, hose or similar object ...
Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022
(MDPI, 2024-03-07)
Background: The declaration of the COVID-19 pandemic triggered global efforts to control and manage the virus impact. Scientists and researchers have been strongly involved in developing effective strategies that can help ...
Robust labeling of human motion markers in the presence of occlusions
(Elsevier, 2019-08-11)
Human motion capture by optical sensors produces snapshots of the motion of a cloud of points that need to be labeled in order to carry out ensuing motion analysis for medical or other purposes. We generate the labeling ...
Variable Speed Wind Turbine Controller Adaptation By Reinforcement Learning
(ACM, 2016-12-30)
The control of Variable Speed Wind Turbines (VSWT) to achieve optimal balance of power generation stability and rotor angular speed is impeded by the non-linear dynamics of the turbine-wind interaction and sudden changes ...
Active Learning for Road Lane Landmark Inventory with V-ELM in Highly Uncontrolled Image Capture Conditions
(Elsevier, 2021-05-28)
Road landmark inventory is becoming an important data product for the maintenance of transport infrastructures. Several commercial sensors are available which include synchronized optical cameras that allowto build 360° ...
Above-ground biomass estimation from LiDAR data using random forest algorithms
(Elsevier, 2022-02)
Random forest (RF) models were developed to estimate the biomass for the Pinus radiata species in a region of the Basque Autonomous Community where this species has high cover, using the National Forest Inventory, allometric ...
Prediction of Aboveground Biomass from Low-Density LiDAR Data: Validation over P. radiata Data from a Region North of Spain
(MDPI, 2019-09-19)
Estimation of forestry aboveground biomass (AGB) by means of aerial Light Detection and Ranging (LiDAR) data uses high-density point sampling data obtained in dedicated flights, which are often too costly for available ...