Automatic Video Summarization Using the Optimum-Path Forest Unsupervised Classifier

Castelo-Fernández, César; Calderón-Ruiz, Guillermo

doi:10.1007/978-3-319-25751-8_91

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Deep Optimum-path Forest1

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Cited by 4 publications

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“…The process is repeated until the last layer is reached. The usage of prototypes as the most representatives samples is supported by the studies of Castelo and Calderón-Ruiz [25] and Afonso et al [26]. Prototypes are located in the regions of highest density and, therefore, are suitable to represent the samples of its cluster [27].…”

Section: Deep Optimum-path Forestmentioning

confidence: 99%

Hierarchical Learning Using Deep Optimum-Path Forest

Afonso,

Pereira,

Weber

et al. 2021

Preprint

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Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson's disease using machine learning and the concept of BoVW. The proposed approach concerns a hierarchical-based learning technique to design visual dictionaries through the Deep Optimum-Path Forest classifier. The proposed method was evaluated in six datasets derived from data collected from individuals when performing handwriting exams. Experimental results showed the potential of the technique, with robust achievements.

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Section: Deep Optimum-path Forestmentioning

confidence: 99%