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Intelligent grading method for walnut kernels based on deep learning and physiological indicators

Overview of attention for article published in Frontiers in Nutrition, January 2023
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Mentioned by

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1 X user

Citations

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5 Dimensions

Readers on

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7 Mendeley
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Title
Intelligent grading method for walnut kernels based on deep learning and physiological indicators
Published in
Frontiers in Nutrition, January 2023
DOI 10.3389/fnut.2022.1075781
Pubmed ID
Authors

Siwei Chen, Dan Dai, Jian Zheng, Haoyu Kang, Dongdong Wang, Xinyu Zheng, Xiaobo Gu, Jiali Mo, Zhuohui Luo

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 14%
Professor 1 14%
Professor > Associate Professor 1 14%
Unknown 4 57%
Readers by discipline Count As %
Unspecified 1 14%
Agricultural and Biological Sciences 1 14%
Engineering 1 14%
Unknown 4 57%
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 05 February 2023.
All research outputs
#20,693,952
of 23,292,144 outputs
Outputs from Frontiers in Nutrition
#3,770
of 4,897 outputs
Outputs of similar age
#331,363
of 422,085 outputs
Outputs of similar age from Frontiers in Nutrition
#373
of 548 outputs
Altmetric has tracked 23,292,144 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,897 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. 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 422,085 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 548 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.