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ULMR: An Unsupervised Learning Framework for Mismatch Removal

Due to radiometric and geometric distortions between images, mismatches are inevitable. Thus, a mismatch removal process is required for improving matching accuracy. Although deep learning methods have been proved to outperform handcraft methods in specific scenarios, including image identification...

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Detalles Bibliográficos
Autores principales:	Deng, Cailong, Chen, Shiyu, Zhang, Yong, Zhang, Qixin, Chen, Feiyan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	MDPI 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413738/ https://www.ncbi.nlm.nih.gov/pubmed/36015871 http://dx.doi.org/10.3390/s22166110

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