Automated Data Selection in the Tau–p Domain: Application to Passive Surface Wave Imaging
Sign Up to like & getrecommendations! Published in 2019 at "Surveys in Geophysics"
DOI: 10.1007/s10712-019-09530-2
Abstract: In the recent decades, passive surface wave methods have gained much attention in the near-surface community due to their ability to retrieve low-frequency surface wave information. Temporal averaging over a sufficiently long period of time… read more here.
Keywords: surface wave; data selection; surface; passive surface ... See more keywords
Data selection methods for Soft Sensor design based on feature extraction
Sign Up to like & getrecommendations! Published in 2020 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2020.12.109
Abstract: Abstract Data selection is a critical issue in data-driven soft sensor design. The paper proposes a new method for data selection based on a feature extraction step, followed by data selection algorithms. The method has… read more here.
Keywords: data selection; soft sensor; selection; feature extraction ... See more keywords
Dataset Optimization for Real-Time Pedestrian Detection
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DOI: 10.1109/access.2017.2788058
Abstract: This paper tackles the problem of data selection for training set generation in the context of near real-time pedestrian detection through the introduction of a training methodology: FairTrain. After highlighting the impact of poorly chosen… read more here.
Keywords: real time; data selection; time; time pedestrian ... See more keywords
Feature Data Selection for Improving the Performance of Entity Similarity Searches in the Internet of Things
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2910736
Abstract: Sensors are used to sense the state information of physical entities in the Internet of Things (IoT). Thus, a large amount of dynamic real-time data is generated. The entity similarity search based on the quantitative… read more here.
Keywords: data selection; entity similarity; feature data; feature ... See more keywords
Cleaning Data With Selection Rules
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DOI: 10.1109/access.2022.3222786
Abstract: In this paper, we propose and study a type of tuple-level constraint that arises from the selection operator $\sigma $ of relational algebra and that closely resembles the concepts of tuple-level denial constraints. We call… read more here.
Keywords: selection rules; data selection; cleaning data; selection ... See more keywords
Data Selection for Multi-Task Learning Under Dynamic Constraints
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DOI: 10.1109/lcsys.2020.3006279
Abstract: Learning-based techniques are increasingly effective at controlling complex systems. However, most work done so far has focused on learning control laws for individual tasks. Simultaneously learning multiple tasks on the same system is still a… read more here.
Keywords: task learning; control; selection multi; data selection ... See more keywords
On Fast Converging Data-Selective Adaptive Filtering
Sign Up to like & getrecommendations! Published in 2019 at "Algorithms"
DOI: 10.3390/a12010004
Abstract: The amount of information currently generated in the world has been increasing exponentially, raising the question of whether all acquired data is relevant for the learning algorithm process. If a subset of the data does… read more here.
Keywords: data selection; adaptive filtering; filtering; fast converging ... See more keywords