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Attention Score in Context
| Title |
From image processing to computational neuroscience: a neural model based on histogram equalization
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, July 2014
|
| DOI | 10.3389/fncom.2014.00071 |
| Pubmed ID | |
| Authors |
Marcelo Bertalmío |
| Abstract |
There are many ways in which the human visual system works to reduce the inherent redundancy of the visual information in natural scenes, coding it in an efficient way. The non-linear response curves of photoreceptors and the spatial organization of the receptive fields of visual neurons both work toward this goal of efficient coding. A related, very important aspect is that of the existence of post-retinal mechanisms for contrast enhancement that compensate for the blurring produced in early stages of the visual process. And alongside mechanisms for coding and wiring efficiency, there is neural activity in the human visual cortex that correlates with the perceptual phenomenon of lightness induction. In this paper we propose a neural model that is derived from an image processing technique for histogram equalization, and that is able to deal with all the aspects just mentioned: this new model is able to predict lightness induction phenomena, and improves the efficiency of the representation by flattening both the histogram and the power spectrum of the image signal. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 4% |
| Germany | 1 | 4% |
| Unknown | 24 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 35% |
| Researcher | 8 | 31% |
| Student > Master | 3 | 12% |
| Professor | 2 | 8% |
| Professor > Associate Professor | 2 | 8% |
| Other | 2 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Mathematics | 6 | 23% |
| Computer Science | 4 | 15% |
| Psychology | 3 | 12% |
| Neuroscience | 3 | 12% |
| Agricultural and Biological Sciences | 2 | 8% |
| Other | 6 | 23% |
| Unknown | 2 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 24 July 2014.
All research outputs
#18,375,064
of 22,758,963 outputs
Outputs from Frontiers in Computational Neuroscience
#1,052
of 1,338 outputs
Outputs of similar age
#146,417
of 204,689 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#15
of 23 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,338 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
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 204,689 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.