Closing the Performance Gap between Siamese Networks for Dissimilarity Image Classification and Convolutional Neural Networks

In this paper, we examine two strategies for boosting the performance of ensembles of Siamese networks (SNNs) for image classification using two loss functions (Triplet and Binary Cross Entropy) and two methods for building the dissimilarity spaces (FULLY and DEEPER). With FULLY, the distance betwee...

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Detalles Bibliográficos
Autores principales: Nanni, Loris, Minchio, Giovanni, Brahnam, Sheryl, Sarraggiotto, Davide, Lumini, Alessandra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433960/
https://www.ncbi.nlm.nih.gov/pubmed/34502700
http://dx.doi.org/10.3390/s21175809

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8433960/
https://www.ncbi.nlm.nih.gov/pubmed/34502700
http://dx.doi.org/10.3390/s21175809

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