Real2sim2real: Self-supervised learning of physical single-step dynamic actions for planar robot casting
This paper introduces the task of Planar Robot Casting (PRC): where one planar motion of a
robot arm holding one end of a cable causes the other end to slide across the plane toward …
robot arm holding one end of a cable causes the other end to slide across the plane toward …
Uncertainty-aware semi-supervised method using large unlabeled and limited labeled COVID-19 data
R Alizadehsani, D Sharifrazi, NH Izadi… - ACM Transactions on …, 2021 - dl.acm.org
The new coronavirus has caused more than one million deaths and continues to spread
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
rapidly. This virus targets the lungs, causing respiratory distress which can be mild or …
Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields
CM Saporetti, DL Fonseca, LC Oliveira… - Marine and Petroleum …, 2022 - Elsevier
The analysis of total organic carbon (TOC) contents is an important activity in exploring
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
potentially hydrocarbon-generating intervals. Petroleum source rocks have, by definition …
Planar robot casting with real2sim2real self-supervised learning
This paper introduces the task of {\em Planar Robot Casting (PRC)}: where one planar
motion of a robot arm holding one end of a cable causes the other end to slide across the …
motion of a robot arm holding one end of a cable causes the other end to slide across the …
Bayesian optimization-based global optimal rank selection for compression of convolutional neural networks
Recently, convolutional neural network (CNN) compression via low-rank decomposition has
achieved remarkable performance. Finding the optimal rank is a crucial problem because …
achieved remarkable performance. Finding the optimal rank is a crucial problem because …
Estimation of natural streams longitudinal dispersion coefficient using hybrid evolutionary machine learning model
Among several indicators for river engineering sustainability, the longitudinal dispersion
coefficient (K x) is the main parameter that defines the transport of pollutants in natural …
coefficient (K x) is the main parameter that defines the transport of pollutants in natural …
Predicting PM2. 5 levels and exceedance days using machine learning methods
Abstract Machine learning methods are increasingly being used in the field of air quality
research to investigate the relationship between air pollutant levels, emissions, and …
research to investigate the relationship between air pollutant levels, emissions, and …
An improved multi-island genetic algorithm and its utilization in the optimal design of a micropositioning stage
W He, X Tang, W Ji, L Meng, J Wei, D Cao, C Ma… - Expert Systems with …, 2024 - Elsevier
An improved multi-island genetic algorithm (IMIGA) by integrating various common
improvement methods, optimized through D-optimal and analysis of variance (ANOVA) …
improvement methods, optimized through D-optimal and analysis of variance (ANOVA) …
Fundamental Components and Principles of Supervised Machine Learning Workflows with Numerical and Categorical Data
SI Kampezidou, A Tikayat Ray, AP Bhat… - Eng, 2024 - mdpi.com
This paper offers a comprehensive examination of the process involved in developing and
automating supervised end-to-end machine learning workflows for forecasting and …
automating supervised end-to-end machine learning workflows for forecasting and …
Active learning for OPM in FMF systems
MA Amirabadi, MH Kahaei… - Physical Communication, 2023 - Elsevier
Optical performance monitoring (OPM) is essential to guarantee the robust and reliable
operation of few-mode fiber (FMF)-based transmission. The available OPM methods …
operation of few-mode fiber (FMF)-based transmission. The available OPM methods …