Concept

Active learning

Related publications (85)

Visual Question Answering is a new task that can facilitate the extraction of information from images through textual queries: it aims at answering an open-ended question formulated in natural language about a given image. In this work, we introduce a new ...

IEEE2021

Transferring interactive activities in large lectures from face-to-face to online settings

Pierre Dillenbourg, Jennifer Kaitlyn Olsen, Louis Pierre Faucon

Purpose Within higher education, there was an abrupt shift from face-to-face to online lecturing with the introduction of social distancing measures in light of a global pandemic. The purpose of this study is to enrich the connection between students and i ...

EMERALD GROUP PUBLISHING LTD2020

Active Improvement of Control Policies with Bayesian Gaussian Mixture Model

Sylvain Calinon, Emmanuel Pignat, Hakan Girgin, Noémie Laure Gwendoline Jaquier

Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In this pa ...

IEEE2020

A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives

Alexander Mathis, Mackenzie Mathis, Steffen Schneider, Jessy Lauer

Extracting behavioral measurements non-invasively from video is stymied by the fact that it is a hard computational problem. Recent advances in deep learning have tremendously advanced our ability to predict posture directly from videos, which has quickly ...

2020

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Objectives This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltration. M ...

SPRINGER2020

Informative sample generation using class aware generative adversarial networks for classification of chest Xrays

Jean-Philippe Thiran

Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem is especially acute, where there is a severe class imbalance. We propose an ...

2019

Detection of curvilinear structures has long been of interest due to its wide range of applications. Large amounts of imaging data could be readily used in many fields, but it is practically not possible to analyze them manually. Hence, the need for automa ...

EPFL2019

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As Saitta et al. report in [1], the flipped classroom model builds on several well-known teaching approaches. In particular, using in-class time for more active learning activities as been constantly shown by research to improve learning [2]. In this prese ...

2019

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While digital tools are more and more used in classrooms, teachers' common practice remains to use photocopied paper documents to share and collect learning exercises from their students. With the Tangible e-Ink Paper (TIP) system, we aim to explore the us ...

ACM2019

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Studying how neural circuits orchestrate limbed behaviors requires the precise measurement of the positions of each appendage in 3-dimensional (3D) space. Deep neural networks can estimate 2-dimensional (2D) pose in freely behaving and tethered animals. Ho ...

2019

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