Search Results for author: Filippo M. Bianchi

Found 5 papers, 1 papers with code

Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images

1 code implementation15 Apr 2020 Luigi T. Luppino, Mads A. Hansen, Michael Kampffmeyer, Filippo M. Bianchi, Gabriele Moser, Robert Jenssen, Stian N. Anfinsen

We propose to extract relational pixel information captured by domain-specific affinity matrices at the input and use this to enforce alignment of the code spaces and reduce the impact of change pixels on the learning objective.

Change Detection Translation

Unsupervised Image Regression for Heterogeneous Change Detection

no code implementations7 Sep 2019 Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser, Stian N. Anfinsen

First, our method quantifies the similarity of affinity matrices computed from co-located image patches in the two images.

Change Detection regression

Deep Divergence-Based Approach to Clustering

no code implementations13 Feb 2019 Michael Kampffmeyer, Sigurd Løkse, Filippo M. Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen

A promising direction in deep learning research consists in learning representations and simultaneously discovering cluster structure in unlabeled data by optimizing a discriminative loss function.

Clustering Deep Clustering +1

Remote sensing image regression for heterogeneous change detection

no code implementations31 Jul 2018 Luigi T. Luppino, Filippo M. Bianchi, Gabriele Moser, Stian N. Anfinsen

In this paper we propose a framework, based on image regression, to perform change detection in heterogeneous multitemporal satellite images, which has become a main topic in remote sensing.

Change Detection Gaussian Processes +1

The Deep Kernelized Autoencoder

no code implementations19 Jul 2018 Michael Kampffmeyer, Sigurd Løkse, Filippo M. Bianchi, Robert Jenssen, Lorenzo Livi

Autoencoders learn data representations (codes) in such a way that the input is reproduced at the output of the network.

Denoising

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