Copernicus 2 Illustration (Source:

The iconic European Programme that provided scientists with the Sentinel missions has something else up its sleeve and this for the decade to come. This article will overview each of the currently studied missions and present which problem they try to address and how they fit in EU policy.

I. Copernicus — What’s that all about ?

The Copernicus Programme, co-managed by the European Commission and the European Space Agency, aims at providing high-quality remote sensing data, on a global scale, for all. This free-of-charge aspect of the data made the programme extremely popular among the community. …

Shanghai Wetland visualised with REACTIV from 2018–01–01 to 2020–09–11

Rapid and EAsy Change detection in radar TIme-series by Variation coefficient

A guest blog post by Thomas Di Martino

Foreword by Sentinel Hub

This post is part of a series of guest blog posts written by script authors, talking about their entries to the Sentinel Hub Custom Script Contest. Thomas Di Martino and his team (Elise Colin-Koeniguer, Regis Guinvarc’h, and Laetitia Thirion-Lefevre) are among the winners in the third round of the Contest. Their winning script with detailed description is available on our GitHub repository.


A performance comparison of three popular techniques (Contrastive, Triplet & Quadruplet loss) used to train similarity learning algorithms on the Quora dataset [1]

Photo by Axel Bonniot on Unsplash

Through this article, I will evaluate and compare three different losses for the task of Deep Similarity Learning. If this topic is still not perfectly understandable to you, I have written an article introducing the main concepts with code examples as well as a complete GitHub repository for you to check:

Table of Content

I. Quick overview of the task

II. Siamese Recurrent Network: similarity learning for sequences

III. Losses for Deep Similarity Learning

IV. Concrete Application: question pairs detection

I. Quick overview of the task

I used for this task the famous Quora question pairs dataset, where the main goal is to predict if two question pairs have…

An in-depth review of a Deep Learning technique for the task of similarity classification.

Photo by Romain Vignes on Unsplash

In this article, I will go through my take on the general concept of Similarity Learning, which processes it involves and how it can be summarized. I will then apply these outlined concepts to the context of sequence similarity detection with question similarities.

Table of Contents

  1. Overview of Similarity Learning
  2. Text Similarity Learning
  3. Source code (PyTorch implementation)

1. Overview of Deep Similarity Learning

When one is doing similarity learning, the same process is always performed:

A quick review of different DL architectures for the TiSeLaC challenge

Presented back in 2017 by the Université de Montpellier, the TiSeLaC challenge [1] (TiSeLaC for Time Series Land Cover) consists in predicting Land Cover class of pixels in Time Series of satellite images.

Photo by Kelly Lacy from Pexels

Table of Contents

  1. What is Time Series Satellite Imagery
  2. What about TiSeLaC dataset ?
  3. TiSeLaC classification task
  4. Conclusion

1. What is Time Series Satellite Imagery?

Time Series Satellite Imagery is the addition of a temporal dimension to Satellite Imagery. …

Thomas Di Martino

As a French PhD student, I am passionate to whatever comes close to Artificial Intelligence and Earth Observation.

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