Tag Archives: Pattern Recognition Letters

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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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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TSS & TSB: Tensor scale descriptors within circular sectors for fast shape retrieval

In this paper, entitled “TSS & TSB: Tensor scale descriptors within circular sectors for fast shape retrieval” and published at the Pattern Recognition Letters Journal, the authors propose a novel region-based descriptors for shape-based image retrieval and analysis. They focus … Continue reading

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Phenological visual rhythms: Compact representations for fine-grained plant species identification

The plant species identification is a key issue for the phenological observation of tree crowns using phenocams. In this paper, entitle “Phenological visual rhythms: Compact representations for fine-grained plant species identification” and published at Pattern Recognition Letters, Volume 81, 2016, … Continue reading

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Fusion of Time Series Representations for Plant Recognition in Phenology Studies

Phenology is one effective way of tracking environmental changes through the study of plant’s periodic events and their relationship to climate. One promising research direction in this area relies on the use of vegetation images to track phenology changes over … Continue reading

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