{rfName}
Em

Indexed in

License and Use

Icono OpenAccess

Citations

28

Altmetrics

Analysis of institutional authors

Jorge, JCorresponding AuthorParedes, RAuthorSanchez, JaAuthor

Share

October 31, 2024
Publications
>
Proceedings Paper
Sí

Empirical Evaluation of Variational Autoencoders for Data Augmentation

Publicated to: PROCEEDINGS OF THE 13TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2018), VOL 5: VISAPP. 5 96-104 - 2018-01-01 5(), DOI: 10.5220/0006618600960104

Authors:

Jorge, J; Vieco, J; Paredes, R; Sanchez, JA; Benedí, JM
[+]

Affiliations

Univ Politecn Valencia, Dept Sistemas Informat & Computat - Author

Abstract

Since the beginning of Neural Networks, different mechanisms have been required to provide a sufficient number of examples to avoid overfitting. Data augmentation, the most common one, is focused on the generation of new instances performing different distortions in the real samples. Usually, these transformations are problem-dependent, and they result in a synthetic set of, likely, unseen examples. In this work, we have studied a generative model, based on the paradigm of encoder-decoder, that works directly in the data space, that is, with images. This model encodes the input in a latent space where different transformations will be applied. After completing this, we can reconstruct the latent vectors to get new samples. We have analysed various procedures according to the distortions that we could carry out, as well as the effectiveness of this process to improve the accuracy of different classification systems. To do this, we could use both the latent space and the original space after reconstructing the altered version of these vectors. Our results have shown that using this pipeline (encoding-altering-decoding) helps the generalisation of the classifiers that have been selected.
[+]

Keywords

Auto encodersClassification systemComputer graphicsComputer visionData augmentationDecodingDifferent mechanismsEmpirical evaluationsEncoder-decoderEncoding (symbols)GeneralisationGenerative modelGenerative modelsLearning systemsSignal encodingVariational autoencoderVector spaces

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-07:

  • WoS: 13
  • Scopus: 15
[+]

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 2026-04-07:

  • The use, from an academic perspective evidenced by the Altmetric agency indicator referring to aggregations made by the personal bibliographic manager Mendeley, gives us a total of: 39.
  • 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: 39 (PlumX).

With a more dissemination-oriented intent and targeting more general audiences, we can observe other more global scores such as:

  • The Total Score from Altmetric: 9.

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.
[+]

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 (Imai, F) and Last Author (BENEDI, JM).

the author responsible for correspondence tasks has been Jorge Cano, Javier.

[+]