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Related publications (30)

Pretraining boosts out-of-domain robustness for pose estimation

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Steffen Schneider

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

Induction of a chromatin boundary in vivo upon insertion of a tad border

Denis Duboule, Lucille Delisle, Christopher Chase Bolt

Author summary During development, enhancer sequences tightly regulate the spatio-temporal expression of target genes often located hundreds of kilobases away. This complex process is made possible by the folding of chromatin into domains, which are separa ...

2021

SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu

The current leading 6D object pose estimation methods rely heavily on annotated real data, which is highly costly to acquire. To overcome this, many works have proposed to introduce computer-generated synthetic data. However, bridging the gap between the s ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Self-Attentive Spatial Adaptive Normalization for Cross-Modality Domain Adaptation

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Guillaume Marc Georges Vray, Devavrat Tomar, Manana Lortkipanidze

Despite the successes of deep neural networks on many challenging vision tasks, they often fail to generalize to new test domains that are not distributed identically to the training data. The domain adaptation becomes more challenging for cross-modality m ...

Institute of Electrical and Electronics Engineers2021

A Characterisation of Alpine Mesocyclone Occurrence

Alexis Berne, Marco Gabella, Monika Feldmann

This work presents a characterisation of mesocyclone occurrence and frequency in the Alpine region, as observed from the Swiss operational radar network; 5 years of radar data are processed with a thunderstorm detection and tracking algorithm and subsequen ...

2021

Aligning the Design of Educational Robotics Tools With Classroom Activities

Francesco Mondada, Christian Giang, Alberto Piatti

This chapter addresses the alignment of educational robotics (ER) tools with classroom activities. To this end, it first introduces a conceptualization of ER activities describing the relevant cognitive artifacts and the learning theories underlying such a ...

IGI Global2021

A compact and cost-effective hard X-ray free-electron laser driven by a high-brightness and low-energy electron beam

Majed Chergui, Christoph Peter Hauri, Christopher Alexander Arrell, Giulia Fulvia Mancini, Leonid Rivkin, Rasmus Ischebeck, Eugenio Ferrari, Camila Bacellar Cases Da Silveira, Mike Seidel, Thomas Schmidt

We present the first lasing results of SwissFEL, a hard X-ray free-electron laser (FEL) that recently came into operation at the Paul Scherrer Institute in Switzerland. SwissFEL is a very stable, compact and cost-effective X-ray FEL facility driven by a lo ...

Nature Publishing Group2020

Sparsely observed functional time series: estimation and prediction

Victor Panaretos, Tomas Rubin

Functional time series analysis, whether based on time or frequency domain methodology, has traditionally been carried out under the assumption of complete observation of the constituent series of curves, assumed stationary. Nevertheless, as is often the c ...

INST MATHEMATICAL STATISTICS2020

Vision based pixel-level bridge structural damage detection using a link ASPP network

Wenlong Deng

Structural Health Monitoring (SHM) has greatly benefited from computer vision. Recently, deep learning approaches are widely used to accurately estimate the state of deterioration of infrastructure. In this work, we focus on the problem of bridge surface s ...

2020

Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

Matthew Josef Parkan

The thesis presented hereby proposes as a general objective the estimation of forest inventory parameters (e.g. trunk location, height, basal area, crown area, species, etc..) from the combination of Airborne Laser Scanning (ALS) and Hyperspectal Imaging ( ...

EPFL2019