Advancing Early Detection of Virus Yellows: Developing a Hybrid Convolutional Neural Network for Automatic Aphid Counting in Sugar Beet Fields. (arXiv:2308.05257v1 [cs.CV])

Aphids are efficient vectors to transmit virus yellows in sugar beet fields.
Timely monitoring and control of their populations are thus critical to prevent
the large-scale outbreak of virus yellows. However, the manual counting of
aphids, which is the most common practice, is labor-intensive and
time-consuming. Additionally, two of the biggest challenges in aphid counting
are that aphids are small objects and their density distributions are varied in
different areas of the field. To address these challenges, we proposed a …

arxiv control convolutional neural network detection fields hybrid monitoring network neural network outbreak scale vectors virus