EdgeNet: An End-to-End Deep Neural Network Pretrained with Synthetic Data for a Real-World Autonomous Driving Application by Leanne Miller, Pedro J. Navarro, Francisca Rosique

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Generating synthetic images for construction machinery data augmentation utilizing context-aware object placement by Yujie Lu, Bo Liu, Wei Wei, Bo Xiao, Zhangding Liu, Wensheng Li

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Improving Image Quality and Controllability in Speed + Angular Velocity to Image Generation Through Synthetic Data for Driving Simulator Generation by Yuto Imai, Tomoya Senda, Yusuke Kajiwara

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Improving doublet cell removal efficiency through multiple algorithm runs by Yong She, Chaoye Wang, Qi Zhao

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LightweightUNet: Multimodal Deep Learning with GAN-Augmented Imaging Data for Efficient Breast Cancer Detection by Hari Mohan Rai, Joon Yoo, Saurabh Agarwal, Neha Agarwal

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