Aug 31, 2020 · Image generation by the conditional generative adversarial network (CGAN) can provide rich samples for supervised classification tasks.
Abstract—Image generation by the conditional generative adversarial network (CGAN) can provide rich samples for super- vised classification tasks.
In this letter, an improved residual condition generation network is proposed to enhance the quality of generated images and classification accuracy for hard ...
Image generation by the conditional generative adversarial network (CGAN) can provide rich samples for supervised classification tasks.
Jan 14, 2024 · Experimental results demonstrate that the proposed approach surpasses existing image translation techniques in terms of both visual effects and ...
The experimental results in this paper demonstrate that CN-GAN has achieved the data generation and data enhancement, the SCNR of generated data is higher ...
... SAR image ship object generation and classification with improved residual conditional generative adversarial network. IEEE Geosci Remote Sens Lett; Li Y, Fu ...
Stage 1 aims to improve the quality and ensure the correctness of the easily generated images. It is implemented by constructing a reinforced constraint ...
A brain-inspired approach for SAR-to-optical image translation ...
www.ncbi.nlm.nih.gov › PMC10861657
Jan 30, 2024 · A sar-to-optical image translation method based on conditional generation adversarial network (cgan). ... Conditional generative adversarial nets.
Results show that the proposed high-resolution SAR ship detection method can make the best use of the original data set, improve the accuracy of ship ...