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1 to 10 of 60 Results

OpenStreetMap land use for Europe "Research Data" Apr 26, 2024 - GIScience / Geoinformatics Research Group Schultz, Michael; Li, Hao; Wu, Zhaoyhan; Wiell, Daniel; Auer, Michael; Zipf, Alexander, 2024, "OpenStreetMap land use for Europe "Research Data"", https://doi.org/10.11588/data/IUTCDN, heiDATA, V1 OSMLanduse data is a scientific dataset generated within the scope of the Horizon 2020 - LandSense project. It is a classification of Sentinel-2 imagery using a deep learning model trained on OSM landuse and landcover features. The data might contain errorneous classifications. T...
Prediction of improvement in Personality Functioning. Utilisation of machine learning to filter relevant variables for prediction [dataset] Mar 4, 2024 - Forschungsgruppe AG Nikendei Rollmann, Ivo; Kindermann, David; Stahl-Toyota, Sophia; Nowak, Jonathan; Orth, Maximilian; Friederich, Hans-Christoph; Nikendei, Christoph, 2024, "Prediction of improvement in Personality Functioning. Utilisation of machine learning to filter relevant variables for prediction [dataset]", https://doi.org/10.11588/data/50WFVL, heiDATA, V1, UNF:6:B4RPojcFDrMxlhi/kXeKpQ== [fileUNF] Introduction. Since its introduction in the DSM-5 and the ICD-11, the construct of personality functioning has received increased research interest. Recent studies have shown that psychotherapy contributes to an improvement in personality functioning. However, it remains unclear...
Integrating VGI contributions for gully mapping using Kalman filter and machine learning Feb 19, 2024 - 3D Spatial Data Processing Vallejo Orti, Miguel; Anders, Katharina; Ajali, Oliubikum; Bubenzer, Olaf; Höfle, Bernhard, 2024, "Integrating VGI contributions for gully mapping using Kalman filter and machine learning", https://doi.org/10.11588/data/UHSQG0, heiDATA, V1, UNF:6:dbfZe/C8CmWXcBEZJg2RPw== [fileUNF] The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of...
Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation Jan 18, 2024 - 3D Spatial Data Processing Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF] This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a...
Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search" Jan 17, 2024 - Natural Language Processing Group Opitz, Juri Alexander, 2024, "Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"", https://doi.org/10.11588/data/RAS7U7, heiDATA, V1 This dataset contains source code and data used in the PhD thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search". The dataset is split into five repositories: S3BERT: Source code to run...
Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins [data] Dec 7, 2023 - HITS MBM Riedmiller, Kai; Reiser, Patrick; Bobkova, Elizaveta; Maltsev, Kiril; Gryn’ova, Ganna; Friederich, Pascal; Gräter, Frauke, 2023, "Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins [data]", https://doi.org/10.11588/data/TGDD4Y, heiDATA, V2 Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the...
Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data] Sep 21, 2023 - Division of Infectious Disease and Tropical Medicine FIND, Geneva, Switzerland, 2023, "Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]", https://doi.org/10.11588/data/CYYNBA, heiDATA, V1 The current four symptom screen recommended by the WHO is widely used as screen to initiate diagnostic testing for active pulmonary tuberculosis (TB), yet the performance is poor especially when TB prevalence is low. In contrast, more sensitive molecular tests are less suitable f...
Accurate classification of major brain cell types using in vivo imaging and neural network processing Sep 18, 2023 - Functional Neuroanatomy Johannes Knabbe, 2023, "Accurate classification of major brain cell types using in vivo imaging and neural network processing", https://doi.org/10.11588/data/L3PITA, heiDATA, V1, UNF:6:j36lvBMAVhENUbq1px2P/Q== [fileUNF] This dataset accompanies the article of the same title in the journal Plos Biology. It includes a) Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation (StardistTraining.tar.gz) b) The trained Stardist nucleus segmentation model (Stardi...
Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code] Jul 20, 2023 - 3D Spatial Data Processing Zahs, Vivien; Anders, Katharina; Kohns, Julia; Stark, Alexander; Höfle, Bernhard, 2023, "Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]", https://doi.org/10.11588/data/D3WZID, heiDATA, V1 Automatic damage assessment by analysing UAV-derived 3D point clouds provides fast information on the damage situation after an earthquake. However, the assessment of different damage grades is challenging given the variety in damage characteristics and limited transferability of...
Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis [data] Jul 7, 2023 - AG Computational Diagnostic Kriegsmann, Mark; Kriegsmann, Katharina; Steinbuss, Georg; Zgorzelski, Christiane; Albrecht, Thomas; Heinrich, Stefan; Farkas, Stefan; Roth, Wilfried; Hausen, Anne; Gaida, Matthias M., 2023, "Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis [data]", https://doi.org/10.11588/data/YAZWJW, heiDATA, V1, UNF:6:gpQyF/jPYXHbW7GvjUboGQ== [fileUNF] Differentiation of neoplastic and non-neoplastic liver lesions using routine histological tissue sections can be challenging. Correct classification is paramount to forecast prognosis and to select the correct therapy. Deep learning algorithms have recently been suggested to supp...

OpenStreetMap land use for Europe "Research Data"

Apr 26, 2024 - GIScience / Geoinformatics Research Group

Schultz, Michael; Li, Hao; Wu, Zhaoyhan; Wiell, Daniel; Auer, Michael; Zipf, Alexander, 2024, "OpenStreetMap land use for Europe "Research Data"", https://doi.org/10.11588/data/IUTCDN, heiDATA, V1

OSMLanduse data is a scientific dataset generated within the scope of the Horizon 2020 - LandSense project. It is a classification of Sentinel-2 imagery using a deep learning model trained on OSM landuse and landcover features. The data might contain errorneous classifications. T...

Prediction of improvement in Personality Functioning. Utilisation of machine learning to filter relevant variables for prediction [dataset]

Mar 4, 2024 - Forschungsgruppe AG Nikendei

Rollmann, Ivo; Kindermann, David; Stahl-Toyota, Sophia; Nowak, Jonathan; Orth, Maximilian; Friederich, Hans-Christoph; Nikendei, Christoph, 2024, "Prediction of improvement in Personality Functioning. Utilisation of machine learning to filter relevant variables for prediction [dataset]", https://doi.org/10.11588/data/50WFVL, heiDATA, V1, UNF:6:B4RPojcFDrMxlhi/kXeKpQ== [fileUNF]

Introduction. Since its introduction in the DSM-5 and the ICD-11, the construct of personality functioning has received increased research interest. Recent studies have shown that psychotherapy contributes to an improvement in personality functioning. However, it remains unclear...

Integrating VGI contributions for gully mapping using Kalman filter and machine learning

Feb 19, 2024 - 3D Spatial Data Processing

Vallejo Orti, Miguel; Anders, Katharina; Ajali, Oliubikum; Bubenzer, Olaf; Höfle, Bernhard, 2024, "Integrating VGI contributions for gully mapping using Kalman filter and machine learning", https://doi.org/10.11588/data/UHSQG0, heiDATA, V1, UNF:6:dbfZe/C8CmWXcBEZJg2RPw== [fileUNF]

The codes and datsets included are related to experiments and results conducted to integrate different lines digitized by volunteers using Kalman filter with changing amount of input lines. Three approaches are included: i) Kalman filtering integration to investigate the role of...

Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation

Jan 18, 2024 - 3D Spatial Data Processing

Weiser, Hannah; Ulrich, Veit; Winiwarter, Lukas; Esmorís, Alberto M.; Höfle, Bernhard, 2024, "Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation", https://doi.org/10.11588/data/UUMEDI, heiDATA, V1, UNF:6:9U7BGTgjjsWd1GduT1qXjA== [fileUNF]

This dataset contains 11 terrestrial laser scanning (TLS) tree point clouds (in .LAZ format v1.4) of 7 different species, which have been manually labeled into leaf and wood points. The labels are contained in the Classification field (0 = wood, 1 = leaf). The point clouds have a...

Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"

Jan 17, 2024 - Natural Language Processing Group

Opitz, Juri Alexander, 2024, "Source code and data for the PhD Thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search"", https://doi.org/10.11588/data/RAS7U7, heiDATA, V1

This dataset contains source code and data used in the PhD thesis "Metrics of Graph-Based Meaning Representations with Applications from Parsing Evaluation to Explainable NLG Evaluation and Semantic Search". The dataset is split into five repositories: S3BERT: Source code to run...

Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins [data]

Dec 7, 2023 - HITS MBM

Riedmiller, Kai; Reiser, Patrick; Bobkova, Elizaveta; Maltsev, Kiril; Gryn’ova, Ganna; Friederich, Pascal; Gräter, Frauke, 2023, "Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins [data]", https://doi.org/10.11588/data/TGDD4Y, heiDATA, V2

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the...

Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]

Sep 21, 2023 - Division of Infectious Disease and Tropical Medicine

FIND, Geneva, Switzerland, 2023, "Diagnostic performance of host protein signatures as a triage test for active pulmonary TB [data]", https://doi.org/10.11588/data/CYYNBA, heiDATA, V1

The current four symptom screen recommended by the WHO is widely used as screen to initiate diagnostic testing for active pulmonary tuberculosis (TB), yet the performance is poor especially when TB prevalence is low. In contrast, more sensitive molecular tests are less suitable f...

Accurate classification of major brain cell types using in vivo imaging and neural network processing

Sep 18, 2023 - Functional Neuroanatomy

Johannes Knabbe, 2023, "Accurate classification of major brain cell types using in vivo imaging and neural network processing", https://doi.org/10.11588/data/L3PITA, heiDATA, V1, UNF:6:j36lvBMAVhENUbq1px2P/Q== [fileUNF]

This dataset accompanies the article of the same title in the journal Plos Biology. It includes a) Ground truth datasets for the training of the StarDist neuronal network for nucleus segmentation (StardistTraining.tar.gz) b) The trained Stardist nucleus segmentation model (Stardi...

Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]

Jul 20, 2023 - 3D Spatial Data Processing

Zahs, Vivien; Anders, Katharina; Kohns, Julia; Stark, Alexander; Höfle, Bernhard, 2023, "Classification of structural building damage grades from multi-temporal photogrammetric point clouds using a machine learning model trained on virtual laser scanning data [Data and Source Code]", https://doi.org/10.11588/data/D3WZID, heiDATA, V1

Automatic damage assessment by analysing UAV-derived 3D point clouds provides fast information on the damage situation after an earthquake. However, the assessment of different damage grades is challenging given the variety in damage characteristics and limited transferability of...

Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis [data]

Jul 7, 2023 - AG Computational Diagnostic

Kriegsmann, Mark; Kriegsmann, Katharina; Steinbuss, Georg; Zgorzelski, Christiane; Albrecht, Thomas; Heinrich, Stefan; Farkas, Stefan; Roth, Wilfried; Hausen, Anne; Gaida, Matthias M., 2023, "Implementation of deep learning in liver pathology optimizes diagnosis of benign lesions and adenocarcinoma metastasis [data]", https://doi.org/10.11588/data/YAZWJW, heiDATA, V1, UNF:6:gpQyF/jPYXHbW7GvjUboGQ== [fileUNF]

Differentiation of neoplastic and non-neoplastic liver lesions using routine histological tissue sections can be challenging. Correct classification is paramount to forecast prognosis and to select the correct therapy. Deep learning algorithms have recently been suggested to supp...

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