Advances in Deep Learning, Artificial Intelligence and Robotics
Springer International Publishing
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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Deep Learning Based Classification System for Recognizing Local Spinach
|
|---|---|
| Book title |
Advances in Deep Learning, Artificial Intelligence and Robotics
|
| Published in |
arXiv, January 2022
|
| DOI | 10.1007/978-3-030-85365-5_1 |
| Book ISBNs |
978-3-03-085364-8, 978-3-03-085365-5
|
| Authors |
Mirajul Islam, Nushrat Jahan Ria, Jannatul Ferdous Ani, Abu Kaisar Mohammad Masum, Sheikh Abujar, Syed Akhter Hossain, Islam, Mirajul, Ria, Nushrat Jahan, Ani, Jannatul Ferdous, Masum, Abu Kaisar Mohammad, Abujar, Sheikh, Hossain, Syed Akhter |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 14% |
| Unknown | 6 | 86% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 7% |
| Student > Doctoral Student | 1 | 7% |
| Student > Master | 1 | 7% |
| Unknown | 11 | 79% |
| Readers by discipline | Count | As % |
|---|---|---|
| Environmental Science | 2 | 14% |
| Unspecified | 1 | 7% |
| Unknown | 11 | 79% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 10 January 2022.
All research outputs
#13,798,575
of 24,093,053 outputs
Outputs from arXiv
#204,377
of 1,018,817 outputs
Outputs of similar age
#206,532
of 505,056 outputs
Outputs of similar age from arXiv
#6,541
of 33,110 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,018,817 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 78% 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 505,056 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.
We're also able to compare this research output to 33,110 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.