Scalable Detection of Fossil Palynomorphs in Multifocal Digital Microscopy Images
研究人员提出首个可扩展的端到端管道，用于在整张玻片图像中自动化检测古植物化石。该方法通过高效分解压缩多焦点显微图像为二维切片、使用 RF-DETR 等模型实现 AP@50 达 0.879 的检测精度、优化大规模图像输出合成及 I/O 处理，将单张玻片的检测时间从数天手动分析缩短至一小时以下。
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The researchers proposed the first scalable end-to-end pipeline for automated detection of palynomorphs in whole slide images. This method efficiently decomposes compressed multi-focus microimages into two-dimensional slices and applies modern target detection models such as RF-DETR, reducing the detection time for a single slide from several days of manual analysis to less than one hour. Experimental results show that the average accuracy (AP@50) on whole slide images reached 0.879, significantly improving the efficiency and automation of palynomorph detection.
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Scalable Detection of Fossil Palynomorphs in Multifocal Digital Microscopy Images
研究人员提出首个可扩展的端到端流水线，用于在整张玻片图像中自动检测古植物化石（Palynomorphs）。该方法通过高效分解压缩多焦点显微图像为二维切片、评估 RF-DETR 等现代目标检测模型（AP@50 达 0.879）、优化大规模图像检测结果合成及 I/O 处理，将单张玻片的检测时间从数天手动分析缩短至一小时以下。