In this project, I explored deep similarity learning algorithms and their behaviour with different types of data (sequential data, spatial data, multimodal data). For each of these different modalities, I wrote 2 Medium article detailing the retained method and providing my implementation.
Thomas Di Martino
PhD Student in AI & Remote Sensing
My research interests include deep learning technologies, automatic feature extraction and computer vision, all of them applied to Remote Sensing problematics, more precisely to Synthetic Aperture Radar (SAR) acquisitions.
Posts
How to choose your loss when designing a Siamese Neural Network ? Contrastive, Triplet or Quadruplet ?
Deep Similarity Learning is the training of a deep learning architecture to learn to detect similarity and disimilarity between two …
Introduction to Deep Similarity Learning for sequences
Deep Similarity Learning is the training of a deep learning architecture to learn to detect similarity and disimilarity between two …
Publications
MSc Thesis: Multimodal Similarity Learning for Duplicate Product Identification
State of the art models for Similarity Learning are all based on Deep Learning architecture using Siamese Network [Gregory et al., …
