e-Spacio es el repositorio institucional en acceso abierto de la UNED que recopila, gestiona, difunde y preserva la producción docente e investigadora de la universidad para fomentar su visibilidad e impacto. Este servicio, ofrecido por la Biblioteca de la UNED, permite a la comunidad universitaria cumplir con lo establecido en la Ley 17/2022 de la Ciencia, la Tecnología y la Innovación, la política de Acceso Abierto de la UNED, los requerimientos de ANECA para las convocatorias de sexenios y acreditaciones, así como con la obligación de publicar en acceso abierto los resultados de los proyectos establecidos por agencias de financiación de la investigación como la Comisión Europea a través de Horizonte Europa.

e-Spacio es recolectado por OpenAire, InvestigaM y Recolecta.

Envíos recientes

Publicación
Deep shared proxy construction hashing for cross-modal remote sensing image fast target retrieval
(ELSEVIER, 2024) han, lirong; Paoletti, Mercedes Eugenia; Moreno Álvarez, Sergio; Haut, Juan M.; Plaza, Antonio; https://orcid.org/0000-0002-8613-7037; https://orcid.org/0000-0003-1030-3729; https://orcid.org/0000-0001-6701-961X; https://orcid.org/0000-0002-9613-1659
The diversity of remote sensing (RS) image modalities has expanded alongside advancements in RS technologies. A plethora of optical, multispectral, and hyperspectral RS images offer rich geographic class information. The ability to swiftly access multiple RS image modalities is crucial for fully harnessing the potential of RS imagery. In this work, an innovative method, called Deep Shared Proxy Construction Hashing (DSPCH), is introduced for cross-modal hyperspectral scene target retrieval using accessible RS images such as optical and sketch. Initially, a shared proxy hash code is generated in the hash space for each land use class. Subsequently, an end-to-end deep hash network is built to generate hash codes for hyperspectral pixels and accessible RS images. Furthermore, a proxy hash loss function is designed to optimize the proposed deep hashing network, aiming to generate hash codes that closely resemble the corresponding proxy hash code. Finally, two benchmark datasets are established for cross-modal hyperspectral and accessible RS image retrieval, allowing us to conduct extensive experiments with these datasets. Our experimental results validate that the novel DSPCH method can efficiently and effectively achieve RS image cross-modal target retrieval, opening up new avenues in the field of cross-modal RS image retrieval
Publicación
Large solutions and gradient bounds for quasilinear elliptic equations
(Taylor and Francis Group, 2015-10-09) Leonori, Tommaso; Porretta, Alessio
Publicación
Comparison principles for p-Laplace equations with lower order terms
(Springer Nature, 2016-08-06) Leonori, Tommaso; Porretta, Alessio; Riey, Giuseppe