Forthcoming articles


International Journal of Adaptive and Innovative Systems


These articles have been peer-reviewed and accepted for publication in IJAIS, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.


Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.


Articles marked with this Open Access icon are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.


Register for our alerting service, which notifies you by email when new issues of IJAIS are published online.


We also offer RSS feeds which provide timely updates of tables of contents, newly published articles and calls for papers.


International Journal of Adaptive and Innovative Systems (1 paper in press)


Regular Issues


  • Multi-Domain Intelligent System for Document Image Retrieval   Order a copy of this article
    by Donato Barbuzzi, Alessandro Massaro, Angelo Galiano, Leonardo Pellicani, Giuseppe Pirlo, Matteo Saggese 
    Abstract: This paper presents an experimental analysis on document image retrieval using a multi-domain intelligent system. More specifically, on the same document image, the combination of three different domains: layout, logo and signature is discussed. This new method analyzes every single decision provided by multi-domain system so that, in the training phase, a new sample classified with a dissimilar confidence to the previous trained samples is used to update the system. DTW, Euclidean Distance and Cosine Similarity have been used, respectively for the analysis of layout, logo and signature. Finally, the weighted combination of individual decisions was considered. The experimental results, carried out on 30 rotated forms belonging to 13 different companies, demonstrate the superiority of the proposed approach with respect to single-domain retrieval systems, based on the ANR performance index. The ANR parameter is able to evaluate the multi-domain system.
    Keywords: Document Management System; Document Image Retrieval; Multi-Expert Intelligent System; Feedback-based strategy; Instance Selection.
    DOI: 10.1504/IJAIS.2016.10011128