- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Benchmarking pre‐trained Encoders for real‐time Semantic Road Scene Segmentation ; volume:20 ; number:1 ; year:2021
Proceedings in applied mathematics and mechanics ; 20, Heft 1 (2021)
- Creator
-
Evers, Lennart
- DOI
-
10.1002/pamm.202000275
- URN
-
urn:nbn:de:101:1-2021020512410526711497
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:34 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Evers, Lennart
Other Objects (12)
Comparability, evaluation and benchmarking of large pre-trained language models
Pre-Trained Driving in Localized Surroundings with Semantic Radar Information and Machine Learning
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset
Offline Pre-trained Multi-agent Decision Transformer
Generalization of vision pre-trained models for histopathology
Leveraging pre-trained language models for code generation
Biomedical event extraction using pre-trained SciBERT
Pre-trained transformer-based language models for Sundanese
Analyzing pre-trained and fine-tuned language models
How to train your pre-trained GAN models
CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey
Comparability, evaluation and benchmarking of large pre-trained language models
Pre-Trained Driving in Localized Surroundings with Semantic Radar Information and Machine Learning
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset
Offline Pre-trained Multi-agent Decision Transformer
Generalization of vision pre-trained models for histopathology
Leveraging pre-trained language models for code generation
Biomedical event extraction using pre-trained SciBERT
Pre-trained transformer-based language models for Sundanese
Analyzing pre-trained and fine-tuned language models
How to train your pre-trained GAN models
CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images
Large-scale Multi-modal Pre-trained Models: A Comprehensive Survey
Comparability, evaluation and benchmarking of large pre-trained language models
Pre-Trained Driving in Localized Surroundings with Semantic Radar Information and Machine Learning
Microstructure segmentation with deep learning encoders pre-trained on a large microscopy dataset
Offline Pre-trained Multi-agent Decision Transformer
Generalization of vision pre-trained models for histopathology
Leveraging pre-trained language models for code generation
Biomedical event extraction using pre-trained SciBERT
Pre-trained transformer-based language models for Sundanese
Analyzing pre-trained and fine-tuned language models
How to train your pre-trained GAN models
CellSeg: a robust, pre-trained nucleus segmentation and pixel quantification software for highly multiplexed fluorescence images