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Deep learning and multiwavelength fluorescence imaging for cleanliness assessment and disinfection in Food Services

Overview of attention for article published in Frontiers in Sensors, September 2022
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1 X user

Citations

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7 Dimensions

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5 Mendeley
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Title
Deep learning and multiwavelength fluorescence imaging for cleanliness assessment and disinfection in Food Services
Published in
Frontiers in Sensors, September 2022
DOI 10.3389/fsens.2022.977770
Authors

Hamed Taheri Gorji, Jo Ann S. Van Kessel, Bradd J. Haley, Kaylee Husarik, Jakeitha Sonnier, Seyed Mojtaba Shahabi, Hossein Kashani Zadeh, Diane E. Chan, Jianwei Qin, Insuck Baek, Moon S. Kim, Alireza Akhbardeh, Mona Sohrabi, Brick Kerge, Nicholas MacKinnon, Fartash Vasefi, Kouhyar Tavakolian

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 20%
Student > Doctoral Student 1 20%
Unknown 3 60%
Readers by discipline Count As %
Computer Science 1 20%
Engineering 1 20%
Unknown 3 60%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2022.
All research outputs
#20,673,680
of 25,392,582 outputs
Outputs from Frontiers in Sensors
#40
of 86 outputs
Outputs of similar age
#320,527
of 434,738 outputs
Outputs of similar age from Frontiers in Sensors
#7
of 17 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 86 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 434,738 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.