Refine
Year of publication
Document Type
- Article (3149)
- Conference Proceeding (1016)
- Part of a Book (184)
- Book (144)
- Doctoral Thesis (30)
- Patent (25)
- Other (9)
- Report (9)
- Preprint (4)
- Poster (3)
- Talk (3)
- Master's Thesis (2)
- Working Paper (2)
- Bachelor Thesis (1)
- Contribution to a Periodical (1)
- Habilitation (1)
Language
- English (4583) (remove)
Has Fulltext
- no (4583) (remove)
Keywords
- Gamification (6)
- avalanche (6)
- Earthquake (5)
- Enterprise Architecture (5)
- MINLP (5)
- solar sail (5)
- Diversity Management (4)
- Energy storage (4)
- Engineering optimization (4)
- LAPS (4)
- Natural language processing (4)
- Papierkunst (4)
- Power plants (4)
- Seismic design (4)
- field-effect sensor (4)
- frequency mixing magnetic detection (4)
- hydrogen (4)
- metal structure (4)
- snow (4)
- steel (4)
Institute
- Fachbereich Medizintechnik und Technomathematik (1545)
- Fachbereich Elektrotechnik und Informationstechnik (686)
- IfB - Institut für Bioengineering (560)
- Fachbereich Energietechnik (552)
- INB - Institut für Nano- und Biotechnologien (532)
- Fachbereich Chemie und Biotechnologie (522)
- Fachbereich Luft- und Raumfahrttechnik (463)
- Fachbereich Maschinenbau und Mechatronik (261)
- Fachbereich Wirtschaftswissenschaften (196)
- Solar-Institut Jülich (160)
- Fachbereich Bauingenieurwesen (146)
- ECSM European Center for Sustainable Mobility (75)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (62)
- Fachbereich Gestaltung (24)
- Nowum-Energy (24)
- Institut fuer Angewandte Polymerchemie (23)
- Sonstiges (21)
- Fachbereich Architektur (20)
- Freshman Institute (18)
- Kommission für Forschung und Entwicklung (18)
Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435.
We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.