Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation

Research article (Computers and Electronics in Agriculture, 2020) · cited 61× · AI/ML
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Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation

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Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimising-realism-of-synthetic-images-using-cycle-generative-adversarial-networks-for-improved-part-segmentation
MLA “Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimising-realism-of-synthetic-images-using-cycle-generative-adversarial-networks-for-improved-part-segmentation.
BibTeX @misc{4ortxyz_optimising-realism-of-synthetic-images-using-cycle-generative-adversarial-networks-for-improved-part-segmentation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimising realism of synthetic images using cycle generative adversarial networks for improved part segmentation}}, year = {2026}, url = {https://4ort.xyz/entity/optimising-realism-of-synthetic-images-using-cycle-generative-adversarial-networks-for-improved-part-segmentation}, note = {Accessed: 2026-05-24}}
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