Modified CycleGAN for the synthesization of samples for wheat head segmentation

arXiv:2402.15135v1 Announce Type: new
Abstract: Deep learning models have been used for a variety of image processing tasks. However, most of these models are developed through supervised learning approaches, which rely heavily on the availability of large-scale annotated datasets. Developing such datasets is tedious and expensive. In the absence of an annotated dataset, synthetic data can be used for model development; however, due to the substantial differences between simulated and real data, a phenomenon referred to as domain gap, the …

abstract arxiv availability cs.ai cs.cv cyclegan datasets deep learning head image image processing processing samples scale segmentation supervised learning tasks through type