| Title |
TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context
|
|---|---|
| Published in |
International Journal of Computer Vision, December 2007
|
| DOI | 10.1007/s11263-007-0109-1 |
| Authors |
Jamie Shotton, John Winn, Carsten Rother, Antonio Criminisi |
Mendeley readers
The data shown below were compiled from readership statistics for 678 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 20 | 3% |
| United Kingdom | 10 | 1% |
| Germany | 9 | 1% |
| Spain | 5 | <1% |
| France | 5 | <1% |
| China | 5 | <1% |
| Switzerland | 4 | <1% |
| Japan | 4 | <1% |
| Italy | 3 | <1% |
| Other | 29 | 4% |
| Unknown | 584 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 260 | 38% |
| Student > Master | 108 | 16% |
| Researcher | 87 | 13% |
| Student > Bachelor | 41 | 6% |
| Student > Doctoral Student | 28 | 4% |
| Other | 83 | 12% |
| Unknown | 71 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 400 | 59% |
| Engineering | 131 | 19% |
| Mathematics | 13 | 2% |
| Earth and Planetary Sciences | 12 | 2% |
| Agricultural and Biological Sciences | 6 | <1% |
| Other | 28 | 4% |
| Unknown | 88 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 23 January 2024.
All research outputs
#4,764,956
of 23,052,509 outputs
Outputs from International Journal of Computer Vision
#202
of 1,166 outputs
Outputs of similar age
#21,973
of 157,575 outputs
Outputs of similar age from International Journal of Computer Vision
#5
of 13 outputs
Altmetric has tracked 23,052,509 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,166 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 70% 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 157,575 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 80% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.