Self-aware and learning structure

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X-ray Micro-CT based characterization of rock cuttings with deep learning

Nils Frédérik Heiden Olsen, Alexandre Massoud Alahi, Pascal Turberg

Rock cuttings from destructive boreholes are a common and cheaper source of drilling materials that can be used to determine underground geology compared to rock core samples. Classifying manually the series of cuttings can be a long and tedious process an ...

2025

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre, Beatrice Vaienti

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

2023

Semi-Supervised Method for Multi-Category Emotion Recognition in Tweets

Pearl Pu Faltings, Claudiu-Cristian Musat, Valentina Sintsova

Each tweet is limited to 140 characters. This constraint surprisingly makes Twitter a more spontaneous platform to express our emotions. Detecting emotions and correctly classifying them automatically is an increasingly important task if we want to underst ...

2014

Perceptual learning, roving and the unsupervised bias

Michael Herzog, Wulfram Gerstner, Carl Kristoffer Aberg, Nicolas Frémaux

Perceptual learning improves perception through training. Perceptual learning improves with most stimulus types but fails when certain stimulus types are mixed during training (roving). This result is surprising because classical supervised and unsupervise ...

Elsevier2012