Recent Submissions 

  1. Panoptic Vision-Language Feature Fields - pre-trained checkpoints 

    Chen, Haoran (2024)
    This file contains the pre-trained model checkpoints used in the experiments on the Replica dataset for the publication "Panoptic Vision-Language Feature Fields". Cf. https://github.com/ethz-asl/pvlff.
    Model
  2. Inferring Implicit 3D Representations from Human Figures on Pictorial Maps 

    Schnürer, Raimund (2023)
    Scikit-learn/TensorFlow/keras/pyTorch Models to estimate 3D poses (baseline), to infer 3D body parts (DISN), to predict UV coordinates (U-Net), to inpaint (coordinate-based) and enhance textures (autoencoder) of pictorial human figures
    Model
  3. Instance Segmentation, Body Part Parsing, and Pose Estimation of Human Figures in Pictorial Maps 

    Schnürer, Raimund (2023)
    TensorFlow/keras models and preprocessed data to idenfity silhouettes of human figures on pictorial maps (Mask R-CNN) and to segment body parts and pose points of pictorial human figures (U-Net)
    Model
  4. Detection of Pictorial Map Objects with Convolutional Neural Networks 

    Schnürer, Raimund (2023)
    keras/TensorFlow models and preprocessed data to classify maps and non-maps (Xception and InceptionResNetV2), to classify pictorial maps and non-pictorial maps (Xception and InceptionResNetV2) as well as to detect sailing ships on historic maps (Faster R-CNN and RetinaNet)
    Model
  5. Polymorphic Control Framework for Rehabilitation Robots - Supplementary Material 

    Sommerhalder, Michael; Zimmermann, Yves; Song, Jaeyong; et al. (2023)
    Model
  6. Magnetotelluric data and 3-D electrical conductivity model of Corbetti volcano in the Main Ethiopian Rift 

    Dambly, Luise; Samrock, Friedemann; Grayver, Alexander; et al. (2023)
    Model
  7. Unsupervised Continual Semantic Adaptation Through Neural Rendering - pre-trained checkpoint 

    Milano, Francesco (2023)
    This is the pre-trained DeepLabv3 checkpoint used in the experiments for the publication "Unsupervised Continual Semantic Adaptation Through Neural Rendering". Cf. https://github.com/ethz-asl/ucsa_neural_rendering/tree/main#deeplabv3-pre-training.
    Model
  8. Model REACT (REgionAl-level_Climate-change_Targets) 

    Tarruella, Marta (2023)
    Model
  9. Ground motion and macroseismic intensity soil amplification maps for Switzerland based on site-condition indicators and incorporating local response as measured at seismic stations 

    Bergamo, Paolo; Fäh, Donat; Panzera, Francesco; et al. (2023)
    This dataset constitutes the soil amplification model for Switzerland presented in the scientific paper “A site amplification model for Switzerland based on site-condition indicators and incorporating local response as measured at seismic stations”, by Paolo Bergamo, Donat Fäh, Francesco Panzera, Carlo Cauzzi, Franziska Glueer, Vincent Perron, Stefan Wiemer, published on “Bulletin of Earthquake Engineering”. The amplification model was ...
    Model
  10. Supplementary materials to: "Printing Homes: Unit Cost Estimation for Additive Manufacturing in Construction" 

    Walzer, Alexander N. (2023)
    Assessing unit costs is crucial for a company's profitability. Recent technological advances in manufacturing may be beneficial for the construction sector, but unit cost assessments are challenging. We propose a deterministic model to assess costs for 3D printed concrete components. The results indicate economies of scale can be achieved. Such findings may help technology suppliers and buyers to make better decisions, eventually increasing ...
    Model
  11. FARMIND InnoFarm 

    Huber, Robert; Späti, Karin (2023)
    The research project InnoFarm evaluated the effectiveness and efficiency of policy programs supporting the adoption of precision agriculture technologies in Swiss agriculture. To do so, we applied the agent-based modelling framework FARMIND (FARM INteraction and Decision Model). This framework was developed by the Agricultural Economics and Policy Group at ETH Zurich (www.aecp.ethz.ch) to simulate farm level decision-making in the context ...
    Model
  12. 3D P-wave Velocity of the Alpine Crust 

    Diehl, Tobias (2023)
    This model repository contains 1D and 3D tomographic P-wave velocity (Vp) models of the Alpine crust. The three-dimensional (3D) model is provided in different formats and its resolution/reliability can be assessed by additional information provided in the repository (Resolution-Diagonal-Elements, Spread-function-values). Details on formats and resolution limits are provided in a README-file included in the repository. Additional information ...
    Model
  13. Code and data availability of PhD thesis 

    Eisenring, Claudia (2023)
    Model
  14. FARMIND AgroCO2ncept 

    Huber, Robert; Kreft, Cordelia Sophie (2023)
    The research project AgroCO2ncept evaluated the effectiveness and efficiency of policy programs supporting the adoption of greenhouse gas mitigation measures in agriculture. To do so, we applied the agent-based modelling framework FARMIND (FARM INteraction and Decision Model). This framework was developed by the Agricultural Economics and Policy Group at ETH Zurich (www.aecp.ethz.ch) to simulate farm level decision-making in the context ...
    Model
  15. Trajectory Optimization Framework for Rehabilitation Robots - Supplementary Material 

    Sommerhalder, Michael; Zimmermann, Yves; Simovic, Leonardo; et al. (2023)
    Model
  16. Functional comparison of metabolic networks across species 

    Ramon, Charlotte; Stelling, Joerg (2023)
    Model

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