  Diabetic Foot Ulcers (DFU) that affect the lower extremities are a major
complication of diabetes. Each year, more than 1 million diabetic patients
undergo amputation due to failure to recognize DFU and get the proper treatment
from clinicians. There is an urgent need to use a CAD system for the detection
of DFU. In this paper, we propose using deep learning methods (EfficientDet
Architectures) for the detection of DFU in the DFUC2020 challenge dataset,
which consists of 4,500 DFU images. We further refined the EfficientDet
architecture to avoid false negative and false positive predictions. The code
for this method is available at
https://github.com/Manugoyal12345/Yet-Another-EfficientDet-Pytorch.
