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Multi-Modal Models for Crop Disease Images by ahmadreza.safara is a document available to read on EtoBox.

The document discusses the development of PhytoSynth, a multi-modal generative model for generating synthetic crop disease images, particularly focusing on watermelon diseases. It highlights the limitations of existing generative adversarial networks (GANs) and presents a novel benchmarking approach for computational requirements and prompt engineering. The research demonstrates that the Stable Diffusion model SD3.5M can efficiently generate high-quality synthetic images from a limited number of real sample

Author
ahmadreza.safara
Language
EN