Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …

Anomaly detection in telemetry channels is a high priority for spacecraft, especially when
considering the harsh environment of space and the magnitude of launch and operation …

Context The emergence rate and growth of maize seedlings are crucial for variety selection
and farm managers; however, the complex planting environment and seedling …

Monitoring tree diseases in forests is crucial for managing pathogens, particularly as climate
change and globalization lead to the emergence and spread of tree diseases. Object …

Yield for biofuel crops is measured in terms of biomass, so measurements throughout the
growing season are crucial in breeding programs, yet traditionally time-and labor …

Deep learning (DL) advancements have contributed to the success of vision-based tasks for
solving real-world problems. DL applications in agriculture are increasing as researchers …

The rise of self-supervised learning (SSL) methods in recent years presents an opportunity
to leverage unlabeled and domain-specific datasets generated by image-based plant …

Plant population counts are highly valued by crop producers as important early-season
indicators of field health. Traditionally, emergence rate estimates have been acquired …

Precision agriculture is a cutting technology in the field for agriculture, which deals with the
challenges of the traditional methodology. This research work is a review of the recent …

In this work, we propose a ladybird beetle detector based on a deep learning classifier and
the weighted Hausdorff distance as a loss function. The detector was trained and validated …