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Published in 2020 at "Extreme Mechanics Letters"
DOI: 10.1016/j.eml.2020.100659
Abstract: Abstract Metamodels, or models of models, map defined model inputs to defined model outputs. Typically, metamodels are constructed by generating a dataset through sampling a direct model and training a machine learning algorithm to predict…
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Keywords:
metamodel;
model;
benchmark dataset;
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Published in 2019 at "Journal of Process Control"
DOI: 10.1016/j.jprocont.2019.04.009
Abstract: Abstract Improvements in sensing, connectivity and computing technologies mean that industrial processes now generate data from a variety of disparate sources. Data may take a number of forms, from time-domain signals, sampled at various rates…
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Keywords:
multiphase flow;
benchmark dataset;
dataset;
heterogeneous benchmark ... See more keywords
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Published in 2024 at "Scientific Data"
DOI: 10.1038/s41597-024-04232-w
Abstract: The global decline in bee populations poses significant risks to agriculture, biodiversity, and environmental stability. To bridge the gap in existing data, we introduce ApisTox, a comprehensive dataset focusing on the toxicity of pesticides to…
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Keywords:
benchmark dataset;
honey bees;
dataset;
new benchmark ... See more keywords
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Published in 2025 at "Scientific Data"
DOI: 10.1038/s41597-025-04772-9
Abstract: This paper presents a large publicly available benchmark dataset (TCMEval-SDT) for the thought process involved in syndrome differentiation in traditional Chinese medicine (TCM). The dataset consists of 300 TCM syndrome diagnosis cases sourced from the…
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Keywords:
diagnosis;
benchmark dataset;
medicine;
tcm ... See more keywords
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Published in 2025 at "Scientific Data"
DOI: 10.1038/s41597-025-05230-2
Abstract: Genome skimming is a promising sequencing strategy for DNA-based taxonomic identification. However, the lack of standardized datasets for benchmarking genome skimming tools presents a challenge in comparing new methods to existing ones. As part of…
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Keywords:
benchmark dataset;
curated benchmark;
genome skimming;
identification ... See more keywords
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Published in 2025 at "Journal of neural engineering"
DOI: 10.1088/1741-2552/ae2714
Abstract: Objective. Automated electroencephalography (EEG)-based epilepsy diagnosis has reported near-perfect accuracies for almost two decades on a benchmark dataset, yet virtually no system is used in routine care. We critically re-examined this translation gap by reproducing…
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Keywords:
diagnosis;
benchmark dataset;
based epilepsy;
artificial intelligence ... See more keywords
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Published in 2024 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2024.3380826
Abstract: Addressing the critical theme of recycling electronic waste (E-waste), this contribution is dedicated to developing advanced automated data processing pipelines as a basis for decision-making and process control. Aligning with the broader goals of the…
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Keywords:
benchmark dataset;
rgb hyperspectral;
pcb vision;
vision ... See more keywords
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Published in 2021 at "IEEE Transactions on Reliability"
DOI: 10.1109/tr.2021.3109122
Abstract: In recent years, technologies of indoor crowd positioning and movement data analysis have received widespread attention in the fields of reliability management, indoor navigation, and crowd behavior monitoring. However, only a few indoor crowd movement…
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Keywords:
movement;
benchmark dataset;
dataset;
movement trajectory ... See more keywords
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Published in 2021 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1009180
Abstract: Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is to associate sensor data into individual crowns. While dozens of crown detection algorithms have been proposed,…
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Keywords:
dataset;
benchmark dataset;
crown detection;
evaluation ... See more keywords
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Published in 2023 at "Entropy"
DOI: 10.3390/e25050794
Abstract: Affective understanding of language is an important research focus in artificial intelligence. The large-scale annotated datasets of Chinese textual affective structure (CTAS) are the foundation for subsequent higher-level analysis of documents. However, there are very…
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Keywords:
affective structure;
structure;
new benchmark;
benchmark dataset ... See more keywords
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Published in 2024 at "Future Internet"
DOI: 10.3390/fi16050174
Abstract: The problem of data enrichment to train visual SLAM and VO construction models using deep learning (DL) is an urgent problem today in computer vision. DL requires a large amount of data to train a…
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Keywords:
benchmark dataset;
tqu slam;
slam;
slam benchmark ... See more keywords