| Title |
A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning
|
|---|---|
| Published in |
Archives of Computational Methods in Engineering, June 2019
|
| DOI | 10.1007/s11831-019-09344-w |
| Authors |
Shaveta Dargan, Munish Kumar, Maruthi Rohit Ayyagari, Gulshan Kumar |
X Demographics
The data shown below were collected from the profiles of 34 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 24% |
| Mexico | 2 | 6% |
| France | 2 | 6% |
| Austria | 2 | 6% |
| China | 1 | 3% |
| Italy | 1 | 3% |
| Comoros | 1 | 3% |
| Korea, Democratic People's Republic of | 1 | 3% |
| Switzerland | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 12 | 35% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 32 | 94% |
| Scientists | 1 | 3% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 981 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 981 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 122 | 12% |
| Student > Master | 119 | 12% |
| Student > Bachelor | 63 | 6% |
| Researcher | 49 | 5% |
| Lecturer | 44 | 4% |
| Other | 135 | 14% |
| Unknown | 449 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 244 | 25% |
| Engineering | 136 | 14% |
| Social Sciences | 16 | 2% |
| Economics, Econometrics and Finance | 12 | 1% |
| Medicine and Dentistry | 11 | 1% |
| Other | 98 | 10% |
| Unknown | 464 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 09 June 2019.
All research outputs
#1,903,333
of 24,290,096 outputs
Outputs from Archives of Computational Methods in Engineering
#5
of 175 outputs
Outputs of similar age
#41,241
of 353,414 outputs
Outputs of similar age from Archives of Computational Methods in Engineering
#1
of 1 outputs
Altmetric has tracked 24,290,096 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 175 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% 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 353,414 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 88% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them