Experimental Results on Synthetic Data Generation in Unreal Engine 5 for Real-World Object Detection-Reference-Cited by-同舟云学术

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Experimental Results on Synthetic Data Generation in Unreal Engine 5 for Real-World Object Detection

Published:2023-06-09 Issue: Volume: Page:
ISSN:
Container-title:2023 17th International Conference on Engineering of Modern Electric Systems (EMES)
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Author:

Damian Alexandru¹,Filip Claudiu¹,Nistor Anamaria¹,Petrariu Irina¹,Mariuc Cătălin¹,Stratan Valentin¹

Affiliation:

1. ASSIST Software,Suceava,Romania

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10171595/10171616/10171761.pdf?arnumber=10171761

Reference16 articles.

1. Domain randomization for transferring deep neural networks from simulation to the real world

2. Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

3. Structured Domain Randomization: Bridging the Reality Gap by Context-Aware Synthetic Data

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Method for Target Detection Based on Synthetic Samples of Digital Twins;IEEE Access;2024

2. A Comparative Analysis of Deep-Learning-Based YOLO Models (V8n and V8s) for Object Detection Using GSV Images;2023 International Conference on Integration of Computational Intelligent System (ICICIS);2023-11-01

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