GIACOMO BORACCHI - TEACHING & THESIS OPPORTUNITIES
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Thesis & Stage Opportunities Thesis related Deep Learning, Computer Vision and Datastream Monitoring Slides updated on September 2022; Presentation Recording, Form to apply for a thesis Research stage opportunities (and thesis in collaboration with companies) are at the end of the above slides Drop me an email if you want to hear about these or latest opportunities!
AY 2022/2023 MSc/BS Courses Artificial Neural Networks and Deep Learning (AN2DL) (Milano Leonardo) Slides and Materials, Calendar and Video Recordings Mathematical Models And Methods For Image Processing (MMMIP) (Milano Leonardo), Materials Informatica A (Milano Leonardo), Ingegneria Matematica: Materiali Calendario Image Analysis and Computer Vision (IACV) (Milano Leonardo, Prof. Vincenzo Caglioti) Materiali
AY 2022/2023 PhD Courses Learning Sparse Representation for Image And Signal Modeling (Milano Leonardo, PhD course) Materials Advanced Deep Learning Models And Methods: The Rise of Transformers (Milano, PhD Course organized by Matteo Matteucci and Giacomo Boracchi) Materials
Past Courses Online Learning and Monitoring (Milano, PhD Course by Giacomo Boracchi and Franceco Trovo') Materials Computer Vision and Pattern Recognition (USI Lugano, MSc course) Materiali Machine Learning For Non-Matrix Data (Lecco, PhD course with guest speakers) Materiali Advanced Deep Learning Models And Methods (Milano, PhD Course organized by Giacomo Boracchi and Matteo Matteucci) Materials Short Course on Learning Sparse Representation for Image And Signal Modeling (Tampere University, PhD course) Materials Advances In Deep Learning With Applications In Text And Image Processing, PhD course organized with Matteo Matteucci (DEIB) and Alessandro Giusti (IDSIA, Lugano) in Polimi Milano Leonardo, February - March 2019. Materials, Detailed Program
Image Classification: Modern Approaches (Milano Leonardo, PhD course, February 2018) Materiali
Informatica (ICMR Lecco, MSc course) Materiali Calendario Informatica B (Milano Bovisa, MSc course): Materiali Calendario
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