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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FusionNet: A Deep Fully Residual Convolutional Neural Network for Image Segmentation in Connectomics
|
|---|---|
| Published in |
arXiv, May 2021
|
| DOI | 10.3389/fcomp.2021.613981 |
| Authors |
Tran Minh Quan, David Grant Colburn Hildebrand, Won-Ki Jeong |
X Demographics
The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 7% |
| Japan | 1 | 7% |
| United States | 1 | 7% |
| Unknown | 12 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 14 | 93% |
| Scientists | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | <1% |
| Luxembourg | 1 | <1% |
| Unknown | 283 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 56 | 20% |
| Student > Master | 50 | 18% |
| Researcher | 31 | 11% |
| Student > Bachelor | 20 | 7% |
| Other | 13 | 5% |
| Other | 32 | 11% |
| Unknown | 83 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 96 | 34% |
| Engineering | 46 | 16% |
| Physics and Astronomy | 7 | 2% |
| Neuroscience | 7 | 2% |
| Agricultural and Biological Sciences | 6 | 2% |
| Other | 26 | 9% |
| Unknown | 97 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 20 February 2024.
All research outputs
#2,209,031
of 25,935,829 outputs
Outputs from arXiv
#34,948
of 956,650 outputs
Outputs of similar age
#55,428
of 457,943 outputs
Outputs of similar age from arXiv
#1,154
of 27,014 outputs
Altmetric has tracked 25,935,829 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 956,650 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 96% of its peers.
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 457,943 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 27,014 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.