[Dec 5th 2018] LabMeeting: Unity: A General Platform for Intelligent Agents

Luca Pasqualini (DIISM, University of Siena) Dec 5, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Recent advances in Deep Reinforcement Learning and Robotics have been driven by the presence of increasingly realistic and complex simulation environments. Many of the existing platforms, however, provide either unrealistic visuals, inaccurate physics, low […]

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[Nov 28th 2018] LabMeeting: Novel Neural Techniques for Gene Expression Analysis in Cancer Prognosis

Gabriele Ciravegna (DIISM, University of Siena) Nov 28, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Cancer is a large family of genetic diseases that involve abnormal cell growth. Genetic mutations can vary from one patient to another. Therefore, personalized precision is required to increase the reliability of prognostic predictions […]

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[Nov 21th 2018] LabMeeting: On confidence measures for deep learning in domain adaptation applications

Simone Bonechi (DIISM, University of Siena) Nov 21, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In recent years, Deep Neural Networks (DNNs) led to impressive results in a wide variety of machine learning tasks, tipically relying on the existence of a huge amount of supervised data. However, in many […]

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[Nov 14th 2018] LabMeeting: High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs

Paolo Andreini (DIISM, University of Siena) Nov 14, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In this seminar a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs) will be presented. Conditional GANs have enabled a variety of applications, but […]

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Winners of soccer data challenge

First Place at SoBigData Soccer Data Challenge

Three of our PhD students Matteo Tiezzi, Dario Zanca, Andrea Zugarini, together with Alessandro Rossi, former PhD student of our lab as well, won the SoBigData Soccer Data Challenge, held in Pisa on October 12-13 during the Internet Festival 2018. The competition was open to people with a passion for data and soccer. For 30 […]

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simone marullo

Simone Marullo Awarded with Pietro Torasso Prize from AI*IA

Simone Marullo, currently student of Computer and Automation Engineering Master Degree at University of Siena, has been awarded with the “Pietro Torasso” prize from the Italian Association for Artificial Intelligence (AI*IA). Popularize Artificial intelligence 2018 – Pietro Torasso Prize was meant to remember Prof. Torasso by encouraging scientific outreach of AI techniques by students. The […]

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lisa graziani awarded

Best Student Paper Award at AI*IA 2018

Lisa Graziani, PhD Student of Universities of Florence and Siena, received best student paper award at AI*IA 2018 (International Conference of the Italian Association for Artificial Intelligence). The awarded paper is “The Role of Coherence in Facial Expression Recognition” written by Lisa Graziani, Stefano Melacci and Marco Gori. It will be presented during the conference, […]

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Facial Expression Recognition

This is still a work-in-progress, but you can try the demo of our Facial Emotion Recognizer based on Convolutional Neural Networks and Learning from Constraints! >> ONLINE DEMO

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[Oct 24th 2018] LabMeeting: Some Approaches to Learning of Logical Constraints

Francesco Giannini (DIISM, University of Siena) Oct 24, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description While learning from constraints is a main topic in artificial intelligence, the problem of learning constraints from exam- ples has received less attention. In this talk, we focus on constraints expressed by logical formulas […]

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dante vs macchina

PoemGen

Is poetry a peculiarity of human beings only? Can machines learn to generate poems that actually convey deep emotional meanings, just like human poets do? A lot of work is still necessary to reach such goal, here we present a simple demo in which we trained two models to generate tercets and verses respectively learning […]

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