Comparison of object detection methods for crop damage assessment using deep learning

Severe weather events can cause large financial losses to farmers. Detailed information on the location and severity of damage will assist farmers, insurance companies, and disaster response agencies in making wise post-damage decisions... (read more)

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Methods used in the Paper


METHOD TYPE
Average Pooling
Pooling Operations
Global Average Pooling
Pooling Operations
Batch Normalization
Normalization
Max Pooling
Pooling Operations
Darknet-19
Convolutional Neural Networks
YOLOv2
Object Detection Models
1x1 Convolution
Convolutions
FPN
Feature Extractors
RPN
Region Proposal
Focal Loss
Loss Functions
RetinaNet
Object Detection Models
Softmax
Output Functions
Convolution
Convolutions
RoIPool
RoI Feature Extractors
Faster R-CNN
Object Detection Models