Deep-learning recognition and tracking of individual nanotubes in low-contrast microscopy videos

• Vladimir Pimonov,
• Said Tahir and
• Vincent Jourdain

Beilstein J. Nanotechnol. 2025, 16, 1316–1324, doi:10.3762/bjnano.16.96

• can be adapted for other types of in situ microscopy studies, emphasizing the importance of automation in high-throughput data acquisition for research on individual nano-objects. Keywords: carbon nanotubes growth kinetics; deep learning; in situ microscopy; object recognition and tracking