8 citations · 8 across the 2 of their papers we have counts for
6 papers
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
Luigi T. Luppino, Mads A. Hansen, Michael Kampffmeyer +4
Image translation with convolutional autoencoders has recently been used as an approach to multimodal change detection in bitemporal satellite images. A main challenge is the align…
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
Luigi Tommaso Luppino, Michael Kampffmeyer, Filippo Maria Bianchi +4
Image translation with convolutional neural networks has recently been used as an approach to multimodal change detection. Existing approaches train the networks by exploiting supe…
Unsupervised Image Regression for Heterogeneous Change Detection
Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser +1
Change detection in heterogeneous multitemporal satellite images is an emerging and challenging topic in remote sensing. In particular, one of the main challenges is to tackle the…
Decision fusion with multiple spatial supports by conditional random fields
Devis Tuia, Michele Volpi, Gabriele Moser
Classification of remotely sensed images into land cover or land use is highly dependent on geographical information at least at two levels. First, land cover classes are observed…
Remote sensing image regression for heterogeneous change detection
Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser +1
Change detection in heterogeneous multitemporal satellite images is an emerging topic in remote sensing. In this paper we propose a framework, based on image regression, to perform…
A clustering approach to heterogeneous change detection
Luigi Tommaso Luppino, Stian Normann Anfinsen, Gabriele Moser +4
Change detection in heterogeneous multitemporal satellite images is a challenging and still not much studied topic in remote sensing and earth observation. This paper focuses on co…