利用相似特征迁移，实现跨蝴蝶亚种的异常检测
Anomaly Detection for Hybrid Butterfly Subspecies via Probability Filtering
- 基于生物分类特征提取，通过概率过滤与颜色抖动增强模拟
- 在新亚种上实现对杂交蝶的准确识别，开发阶段排名第二
- 适合需要跨物种泛化的异常检测场景
检测蝴蝶杂交个体需依赖亲本亚种知识，面对新亚种时过程繁琐。本研究聚焦于模型训练后可迁移至生物学特征相似的另一亚种场景：当亚种A与亚种B具有相似外观模式时，采用BioCLIP作为特征提取器，捕捉其分类学特征。由于两者杂交与非杂交模式关系一致，原针对亚种A设计的算法可有效迁移到亚种B。为判断蝴蝶是否为杂交，提出概率过滤结合颜色抖动进行数据增强与模仿模拟。该方法在官方开发阶段取得第二名成绩。代码已公开于 https://github.com/Justin900429/NSF-HDR-Challenge。
原文摘要 · Abstract (English)
Detecting butterfly hybrids requires knowledge of the parent subspecies, and the process can be tedious when encountering a new subspecies. This study focuses on a specific scenario where a model trained to recognize hybrid species A can generalize to species B when B biologically mimics A. Since species A and B share similar patterns, we leverage BioCLIP as our feature extractor to capture features based on their taxonomy. Consequently, the algorithm designed for species A can be transferred to B, as their hybrid and non-hybrid patterns exhibit similar relationships. To determine whether a butterfly is a hybrid, we adopt proposed probability filtering and color jittering to augment and simulate the mimicry. With these approaches, we achieve second place in the official development phase. Our code is publicly available at https://github.com/Justin900429/NSF-HDR-Challenge.
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