| Title |
Automated defect inspection of LED chip using deep convolutional neural network
|
|---|---|
| Published in |
Journal of Intelligent Manufacturing, March 2018
|
| DOI | 10.1007/s10845-018-1415-x |
| Authors |
Hui Lin, Bin Li, Xinggang Wang, Yufeng Shu, Shuanglong Niu |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 118 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 19% |
| Student > Master | 18 | 15% |
| Researcher | 11 | 9% |
| Student > Doctoral Student | 7 | 6% |
| Lecturer | 5 | 4% |
| Other | 16 | 14% |
| Unknown | 39 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 35 | 30% |
| Computer Science | 34 | 29% |
| Business, Management and Accounting | 2 | 2% |
| Agricultural and Biological Sciences | 1 | <1% |
| Environmental Science | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 41 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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
#2,800,864
of 25,008,338 outputs
Outputs from Journal of Intelligent Manufacturing
#3
of 628 outputs
Outputs of similar age
#56,880
of 335,134 outputs
Outputs of similar age from Journal of Intelligent Manufacturing
#1
of 5 outputs
Altmetric has tracked 25,008,338 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 628 research outputs from this source. They receive a mean Attention Score of 1.4. This one has done particularly well, scoring higher than 99% 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 335,134 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 82% of its contemporaries.
We're also able to compare this research output to 5 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