41 to 50 of 121 Results
Nov 2, 2016
Hier finden Sie Forschungsdaten und weiteres Material zu Artikeln aus Perspektive Bibliothek. |
Jun 16, 2014 - Statistical Natural Language Processing Group
Wäschle, Katharina; Riezler, Stefan, 2014, "PatTR: Patent Translation Resource", https://doi.org/10.11588/data/10002, heiDATA, V3
PatTR is a sentence-parallel corpus extracted from the MAREC patent collection. The current version contains more than 22 million German-English and 18 million French-English parallel sentences collected from all patent text sections as well as 5 million German-French sentence pa... |
Oct 26, 2020 - OwnReality. To Each His Own Reality
Schepp, Moritz, 2020, "OwnReality API-only web application", https://doi.org/10.11588/data/KZHLS8, heiDATA, V1
This dataset contains the data platform for the research project "OwnReality. To Each His Own Reality". During the course of the project, data was gathered and entered into a database. In general, this platform allows the integration of that data into web based systems such as co... |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "Opinion role extractor", https://doi.org/10.11588/data/3W7AQP, heiDATA, V1
System for the Extraction of Subjective Expressions, Sentiment Sources and Sentiment Targets from German Text |
Jul 27, 2021 - Institute of Pathology Mannheim
Runz, Marlen; Weis, Cleo-Aron, 2021, "Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks [Dataset]", https://doi.org/10.11588/data/8LKEZF, heiDATA, V1
Here we provide the data sets supporting the experiments in our publication Normalization of HE-Stained Histological Images using Cycle Consistent Generative Adversarial Networks, which were collected at the Institute of Pathology, Medical Faculty Mannheim, Heidelberg University.... |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]", https://doi.org/10.11588/data/PCGYET, heiDATA, V1
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC. For more information, also see the code documentation: https://github.com/vislearn/ngransac |
Nov 13, 2023Empirical Linguistics and Computational Language Modeling (LiMo)
Research Data to the PhD Projects of Ngoc Do. |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Neural Rerankers for Dependency Parsing", https://doi.org/10.11588/data/NNGPQZ, heiDATA, V1
This resource contains code for different types of neural rerankers (RCNN, RCNN-shared and GCN) from the paper: Do and Rehbein (2020). "Neural Reranking for Dependency Parsing: An Evaluation". We also include in this resource the pre-trained models of different rerankers on 3 lan... |
Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Neural PP Attachment Disambiguation Systems", https://doi.org/10.11588/data/DKWKGJ, heiDATA, V1
This resource contains code for different types of neural PP attachment disambiguation systems: A disambiguation system inspired by de Kok et al. (2017) but with the ranking loss function. A disambiguation system with biaffine attention similar to the neural dependency parser in... |