Category Archives: publications

scholarly publications of RECOD members

Empirical Evaluation of Resampling Procedures for Optimising SVM Hyperparameters

Tuning the regularisation and kernel hyperparameters is a vital step in optimising the generalisation performance of kernel methods, such as the support vector machine (SVM). This is most often performed by minimising a resampling/cross-validation based model selection criterion, however there … Continue reading

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Empirical comparison of cross-validation and internal metrics for tuning SVM hyperparameters

Hyperparameter tuning is a mandatory step for building a support vector machine classifier. In this article, the authors study some methods based on metrics of the training set itself, and not the performance of the classifier on a different test … Continue reading

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Video pornography detection through deep learning techniques and motion information

In this paper, the authors deal with a growing issue of our connected society: automated sensitive media (pornographic, violent, gory, etc.) filtering. A range of applications has increased societal interest on the problem, e.g., detecting inappropriate behavior via surveillance cameras; … Continue reading

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RECOD wins international competition for melanoma classification

A team of RECOD researchers won the melanoma classification task at the “Skin Lesion Analysis towards Melanoma Detection” challenge promoted by the International Skin Imaging Collaboration (ISIC). RECOD got the third place (among 23 participants) at the skin lesion classification … Continue reading

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A graph-based ranked-list model for unsupervised distance learning on shape retrieval

Several re-ranking algorithms have been proposed recently. Some effective approaches are based on complex graph-based diffusion processes, which usually are time consuming and therefore inappro- priate for real-world large scale shape collections. In this article, the authors present a novel … Continue reading

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A correlation graph approach for unsupervised manifold learning in image retrieval tasks

In this paper, the authors Daniel Pedronette and Ricardo Torres, discuss a novel unsupervised manifold learning algorithm, which aims at imitating the human behavior in judging similarity among images. The proposed algorithm exploits unlabeled contextual information encoded in the dataset … Continue reading

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On the Reconstruction of Text Phylogeny Trees: Evaluation and Analysis of Textual Relationships

In this article, recently accepted at PLOS ONE journal and available as open access, the authors propose a framework for reconstructing text evolutionary trees, aiming at reconstructing the history of modifications that a set of related documents has gone through. … Continue reading

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On Interactive Learning-to-Rank for IR: Overview, Recent Advances, Challenges, and Directions

In this article, the authors deal with the problem of creating interactive information retrieval (IIR) systems nowadays. The work reviews several interactive retrieval related aspects focusing mainly on recent advances, important challenges and promising research directions. The paper shows that, … Continue reading

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Modeling plant phenology database: Blending near-surface remote phenology with on-the-ground observations

The study of recurrent life cycles events and its relationship to climate, plant phenology, handles multifaceted information that needs to be organized and made promptly accessed by scientific community. In this paper, the authors propose the conceptual design and implementation … Continue reading

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A multimodal query expansion based on genetic programming for visually-oriented e-commerce applications

The article entitled “A multimodal query expansion based on genetic programming for visually-oriented e-commerce applications” presents a novel multimodal query expansion strategy, based on genetic programming (GP), for image search in visually-oriented e-commerce applications. The proposed solution allows finding relevant … Continue reading

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