HIGHLIGHTS
- What: By reducing the model`s parameter count and focusing on more efficient feature extraction methods, this approach shows high compatibility with low-power devices by reducing memory and processing load without sacrificing accuracy.
- Who: Tarun Belwal et al. from the Texas A and M University, United States have published the research: A lightweight MHDI-DETR model for detecting grape leaf diseases, in the Journal: (JOURNAL)
- How: This method was evaluated on both the Plant Village dataset and images collected from orchards in the field with experimental results showing improvements of 5.94 . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.