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Jan 15, 2020 - 3D Spatial Data Processing
Herfort, Benjamin; Anders, Katharina; Marx, Sabrina; Eberlein, Stefan; Höfle, Bernhard, 2020, "3D Micro-Mapping of Subsidence Stations [Source Code and Data]", https://doi.org/10.11588/data/OU8YA1, heiDATA, V1
This dataset comprises the source code to reproduce the 3D micro-mapping tool for plane adjustment at subsidence stations. In this project, users adjust a plane (height and orientation) at the positions of fixed poles, so-called subsidence stations, to provide information on the... |
Jul 21, 2022 - 3D Spatial Data Processing
Shinoto, Maria; Doneus, Michael; Haijima, Hideyuki; Weiser, Hannah; Zahs, Vivien; Kempf, Dominic; Daskalakis, Gwydion; Höfle, Bernhard; Nakamura, Naoko, 2022, "3D Point Cloud from Nakadake Sanroku Kiln Site Center, Japan: Sample Data for the Application of Adaptive Filtering with the AFwizard", https://doi.org/10.11588/data/TJNQZG, heiDATA, V2
This data set represents 3D point clouds acquired with LiDAR technology and related files from a subregion of 150*436 sqm in the ancient Nakadake Sanroku Kiln Site Center in South Japan. It is a densely vegetated mountainous region with varied topography and vegetation. The data... |
Nov 23, 2022 - Institute of Organic Chemistry - AK Mastalerz
Yang, Xuan; Elbert, Sven Michael; Rominger, Frank; Mastalerz, Michael, 2022, "A Series of Soluble Thieno-fused Coronene Nanoribbons of Precise Lengths [Data]", https://doi.org/10.11588/data/30AOAT, heiDATA, V1
Among graphene nanoribbons (GNRs), reports on coronene-based GNRs were very rare, despite the unique optoelectronic properties of coronene. Herein, the synthesis of a series of structurally precise and soluble thieno-fused coronene nanoribbons (CR-1 to CR-4) with up to four coron... |
Feb 4, 2019 - AIPHES
Marasovic, Ana, 2019, "Abstract Anaphora Resolution [Source Code]", https://doi.org/10.11588/data/UDMPY5, heiDATA, V1
Abstract Anaphora Resolution (AAR) aims to find the interpretation of nominal expressions (e.g., this result, those two actions) and pronominal expressions (e.g., this, that, it) that refer to abstract-object-antecedents such as facts, events, plans, actions, or situations. The f... |
May 13, 2024 - 3D Spatial Data Processing
Vallejo-Orti, Miguel; Winiwarter, Lukas; Corral, Eva; Williams, Jack; Bubenzer, Olaf; Höfle, Bernhard, 2024, "An Automatic Iterative Random Forest approach to derive gully activity maps in large areas with training data scarcity [Data and Source Code]", https://doi.org/10.11588/data/WGAU4Q, heiDATA, V1
Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1, and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micro-mapping simulation as training... |
Apr 12, 2021 - Institute of Medical Psychology
Warth, Marco, 2021, "Biographical music therapy in palliative care [dataset]", https://doi.org/10.11588/data/Z4XZQ7, heiDATA, V1, UNF:6:Nt/CiJX5oFRkCInlnHZ+Xw== [fileUNF]
1. PURPOSE: Awareness for the importance of psychological and spiritual needs in patients with terminal diseases has increased in recent years. While clinical trials have demonstrated the potential of psychosocial interventions in cancer populations, it remains a challenge to tra... |
Feb 6, 2019 - AIPHES
Heinzerling, Benjamin, 2019, "BPEmb: Pre-trained Subword Embeddings in 275 Languages (LREC 2018)", https://doi.org/10.11588/data/V9CXPR, heiDATA, V1
BPEmb is a collection of pre-trained subword unit embeddings in 275 languages, based on Byte-Pair Encoding (BPE). In an evaluation using fine-grained entity typing as testbed, BPEmb performs competitively, and for some languages better than alternative subword approaches, while r... |
Asan, Livia; Falfán-Melgoza, Claudia; Beretta, Carlo Antonio; Sack, Markus; Zheng, Lei; Weber-Fahr, Wolfgang; Kuner, Thomas; Knabbe, Johannes, 2021, "Cellular correlates of gray matter volume changes in magnetic resonance morphometry identified by two-photon microscopy [Dataset]", https://doi.org/10.11588/data/04HPWW, heiDATA, V1, UNF:6:t1jhJE4myjockvvIVpnP7A== [fileUNF]
This dataset accompanies the article of the same title in the journal Scientific Reports. It includes a) spreadsheets of data values for each plot in the main figures, b) all raw image data from Two-Photon in vivo microscopy (2pii) c) Custom code d) representative subsets of segm... |
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... |
Jan 16, 2024 - 3D Spatial Data Processing
Vallejo Orti, Miguel; Castillo, Carlos; Zahs, Vivien; Bubenzer, Olaf; Höfle, Bernhard, 2023, "Classification of Types of Changes in Gully Environments Using Time Series Forest Algorithm [data]", https://doi.org/10.11588/data/NSMM6P, heiDATA, V2, UNF:6:KVUhApCn+Ker99oncknXzA== [fileUNF]
This code implements the TimeSeriesForest algorithm to classify different types of changes in gully environments. i)gully topographical change, ii)no change outside gully, iii) no change inside gully, and iv) non-topographical change. The algorithm is specifically designed for ti... |
