Improvised Aerial Object Detection approach for YOLOv3 Using Weighted Luminance

Aerial imaging of ground targets is highly challenging because of various factors that affect light propagation through different mediums. Several convolutional neural network-based object detection algorithms that are developed require more robustness when applied in the field of aerial imaging and remote sensing.

Data and Resources

Cite this as

Sai Ganesh CSa, Aouthithiye Barathwaj SR Ya, Swethaa Sb, R. Azhagumurugana (2024). Dataset: Improvised Aerial Object Detection approach for YOLOv3 Using Weighted Luminance. https://doi.org/10.57702/bbtsbczs

DOI retrieved: December 2, 2024

Additional Info

Field Value
Created December 2, 2024
Last update December 2, 2024
Author Sai Ganesh CSa
More Authors
Aouthithiye Barathwaj SR Ya
Swethaa Sb
R. Azhagumurugana