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Analysis of institutional authors

Sanchez, ACorresponding AuthorMoreno, AbAuthorVelez, DAuthor

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September 27, 2022
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Analyzing the influence of contrast in large-scale recognition of natural images

Publicated to:Integrated Computer-Aided Engineering. 23 (3): 221-235 - 2016-01-01 23(3), DOI: 10.3233/ICA-160516

Authors: Sanchez, Angel; Belen Moreno, A; Velez, Daniel; Veleza, Jose F

Affiliations

Univ Complutense, Dept Stat & Operat Res 1, Ciudad Univ, Madrid, Spain - Author
Univ Rey Juan Carlos, Dept Comp Sci & Stat, Campus Mostoles,C Tulipan,S-N, Mostoles 28933, Madrid, Spain - Author

Abstract

This paper analyzes both the isolated influence of illumination quality in 2D facial recognition and also the influence of contrast measures in large-scale recognition of low-resolution natural images. First, using the Yale Face Database B, we have shown that by separately estimating the illumination quality of facial images (through a fuzzy inference system that combines average brightness and global contrast of the patterns) and by recognizing the same images using a multilayer perceptron, there exists a nearly-linear correlation between both illumination and recognition results. Second, we introduced a new contrast measure, called Harris Points Measured Contrast (HPMC), which assigns values of contrast in a more consistent form to images, according to their recognition rate than other global and local compared contrast analysis methods. For our experiments on image contrast analysis, we have used the CIFAR-10 dataset with 60,000 images and convolutional neural networks as classification models. Our results can be considered to decide if it is worth using a given test image, according to its calculated contrast applying the proposed HPCM metric, for further recognition tasks.

Keywords

2d face imagesCifar-10 imagesClassification (of information)Contrast measuresConvolutionConvolutional neural networkFace imagesFace recognitionFuzzy inferenceImage analysisImage qualityImage quality assessmentMultilayer neural networksMultilayer perceptronMultilayersNeural networksPattern recognition systemsQuality assessment

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Integrated Computer-Aided Engineering due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2016, it was in position 1/85, thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering, Multidisciplinary.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 4.65, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Aug 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-08-22, the following number of citations:

  • WoS: 15
  • Scopus: 16

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-08-22:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 5 (PlumX).

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Sánchez Calle, Ángel) and Last Author ().

the author responsible for correspondence tasks has been Sánchez Calle, Ángel.