Problem
Research questions and friction points this paper is trying to address.
long-tailed datasets
rare taxa
plankton imaging
Multimodal Taxonomic Conditioning for Generative Plankton Imagery
🤖 AI Summary
为解决稀有浮游生物图像不足问题，通过改进CLIP编码器并结合扩散变换器生成合成浮游生物图像。
📝 Abstract
Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or evaluate classifiers reliably. We generate synthetic plankton imagery conditioned on taxonomy: a CLIP encoder is adapted on a large plankton corpus with a ranked contrastive objective extended to deep, ragged taxonomies, then frozen to condition a parameter-efficient diffusion transformer. We evaluate synthetic sample quality on distributional fidelity and downstream classifier utility.
Innovation
Methods, ideas, or system contributions that make the work stand out.
multimodal taxonomic conditioning
synthetic plankton imagery
CLIP encoder
ranked contrastive objective
diffusion transformer
🔎 Similar Papers
No similar papers found.
