DetectNano: Deep Learning Detection in TEM Images for High-Throughput Polymer Nanostructure Characterization

The rapid and unbiased characterization of self-assembled polymeric vesicles in transmission electron microscopy (TEM) images remains a challenge in polymer science. Here, we present a deep learning-powered detection framework based on YOLOv8, enhanced with Weighted Box Fusion, to automate the identification and size estimation of polymer nanostructures. By incorporating multiple morphologies in the training dataset, we improve model generalization and achieve robust detection across unseen TEM images. Our results demonstrate that the model provides accurate vesicle detection in under 2 seconds—an efficiency unattainable by traditional image analysis software. The proposed framework enables reproducible and scalable nano-objects characterization, paving the way for a general AI-driven automation in polymer self-assembly research.