Automatic Hand Phantom Map Detection Methods

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Author summaryForecasting the short time evolution of the COVID-19 daily incidence is a key issue in the epidemic decision making policy. We propose a machine learning method which forecasts the future values of the daily incidence trend based on the evolu ...

Humans and animals constantly adapt to their environment over the course of their life. This thesis seeks to integrate various timescales of adaptation, ranging from the adaptation of synaptic connections between spiking neurons (milliseconds), rapid behav ...

Data-driven approaches based on high-throughput capabilities and machine learning hold promise in revolutionizing human-centred materials discovery for sustainability and decarbonization. This Review examines the strengths and limitations of different trad ...

Aging civil infrastructures are closely monitored by engineers for damage and critical defects. As the manual inspection of such large structures is costly and time-consuming, we are working towards fully automating the visual inspections to support the pr ...

Advances in computing have enabled widespread access to pose estimation, creating new sources of data streams. Unlike mock set-ups for data collection, tapping into these data streams through on-device active learning allows us to directly sample from the ...

The learning process depends on the nature of the learning environment, particularly in the case of open-ended learning environments, where the learning process is considered to be non-linear. In this paper, we report on the findings of employing a multimo ...

The trend towards generalized blended and active learning approaches in engineering education is redefining the requirements and the deployment schemes for digital education platforms. This paper presents a quadriptych techno- pedagogical model highlightin ...

In superstructure optimization of processes and energy systems, the design space is defined as the combination of unit considerations, process conditions and model parameters that might be subjected to uncertainty. Most of the time, decision makers are not ...

In this paper we study the problem of social learning under multiple true hypotheses and self-interested agents. In this setup, each agent receives data that might be generated from a different hypothesis (or state) than the data other agents receive. In c ...

Background and objective The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time ...

Computational thinking (CT) skills are becoming increasingly relevant for future professionals across all domains, beyond computer science (CS). As such, an increasing number of bachelor and masters programs outside of the computer science discipline integ ...

Automatic Hand Phantom Map Detection Methods

Chattez avec Graph Search

Learning from the past: A short term forecast method for the COVID-19 incidence curve

From event-based surprise to lifelong learning. A journey in the timescales of adaptation

Human- and machine-centred designs of molecules and materials for sustainability and decarbonization

Active Learning for Imbalanced Civil Infrastructure Data

VL4Pose: Active Learning Through Out-Of-Distribution Detection For Pose Estimation

Temporal Pathways to Learning: How Learning Emerges in an Open-ended Collaborative Activity

Integrated Model for Comprehensive Digital Education Platforms

Active learning for multi-objective optimization of processes and energy systems

Social Learning with Disparate Hypotheses

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation

Promoting Computational Thinking Skills in Non-Computer Science Students Gamifying Computational Notebooks to Increase Student Engagement