[Mar 27th 2019]: Jumping Finite Automata

Prof. Alexander Meduna is a theoretical computer scientist and expert on compiler design, formal languages and automata. He is a professor of Computer Science at the Brno University of Technology. Mar 27, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description This talk proposes a new investigation area in automata theory […]

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[Mar 20th 2019] Lab Meeting: Towards laws of visual attention

Dario Zanca (DIISM, University of Siena) Mar 20, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description When eye-tracking devices are not a viable option, models of visual attention can be used to predict locations fixated by humans. We argue that the idea of a saliency map is ill-posed, and present […]

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[Mar 13th 2019] Lab Meeting: Integrating Learning and Reasoning with Deep Logic Models

Francesco Giannini (DIISM, University of Siena) Mar 13, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Deep learning is very effective at jointly learning feature representations and classification models, especially when dealing with high dimensional input patterns. Probabilistic logic reasoning, on the other hand, is capable to take consistent and […]

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[Mar 6th 2019] LabMeeting: A Deep Learning Models Comparison for Brain Age Estimation

Simone Bonechi (DIISM, University of Siena) Mar 6, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In recent years, deep learning and Convolutional Neural Networks (CNNs) have produced a devastating impact on computer vision, achieving outstanding results on a variety of problems, including medical image analysis. Recently, these techniques have […]

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[Feb 27th 2019] LabMeeting: Supervision Generation for Scene Text Segmentation with Multiscale Attention Networks

Paolo Andreini (DIISM, University of Siena) Feb 27, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In this seminar, a novel approach to scene text segmentation is presented. The method exploits a new convolutional neural network model, called Segmentation Multiscale Attention Network (SMANet). Employing the SMANet the COCO–Text–Segmentation (COCO TS) […]

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[Feb 20th 2019] Increasing machine autonomy and ethics

Guglielmo Tamburrini, Università di Napoli Federico II. Feb 20, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description The rise of increasingly autonomous AI and robotic systems is bringing about a variety of novel and impending ethical issues. These include the issue whether certain forms of machine autonomy are morally admissible, […]

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[Feb 20th 2019] Explaining the behavior of learning classification systems: a model agnostic approach

Roberto Prevete, Università di Napoli Federico II. Feb 20, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description It is difficult to reconstruct and exhaustively explain the decisions/behaviors of current autonomous or semi-autonomous systems based on Machine Learning techniques. This characteristic is due to the fact that they usually do not […]

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[Jan 30th 2019] Designing non-parametric activation functions: recent advances

Simone Scardapane and Aurelio Uncini (Università Sapienza) Jan 30, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Recently, the design of flexible nonlinearities has become an important line of research in the deep learning community. In the first part of the talk we will review how to tackle this problem, […]

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[Jan 23rd 2019] LabMeeting: Invertible conditional GANs

Lisa Graziani (DIISM, University of Siena) Jan 23, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Generative Adversarial Networks (GANs) allow to generate images and are used in a variety of applications, as image synthesis, semantic image editing, style transfer, image super-resolution, image transformation and classification. Relevant extensions of GANs […]

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