Skip to content
All publications
PaperSubmitted1 min read

HybridVirusNet: A Hybrid Detection–Classification Framework for Multi-Class Virus Identification in TEM Images

A hybrid detection–classification framework for multi-class virus identification in transmission electron microscopy images — submitted to Springer Nature Journal of Biomedical Science.

Md Mahmudul HoqueSpringer Nature Journal of Biomedical Science

Submitted to Springer Nature Journal of Biomedical Science. Under peer review — not yet published.

Focus

Transmission electron microscopy (TEM) remains a primary way to inspect virus morphology. HybridVirusNet combines detection and classification stages so multi-class virus identification can be approached as one pipeline rather than disconnected models.

Topics

  • Virology
  • TEM imaging
  • Hybrid detection–classification models

Authors and venue are as listed in the Lab record. Results and acceptance status will be recorded here only once they are public.