Table 1.
Summary of literature review.
Fig 1.
Block diagram of the system.
Table 2.
UAV test specifications.
Fig 2.
Nvidia Jetson Nano embedded AI computer.
Fig 3.
The structure of deep learning.
Fig 4.
Architecture of CNN.
Fig 5.
Architecture of RNN.
Fig 6.
CNN-RCNN model.
Table 3.
Hyperparameters of the proposed models.
Fig 7.
General structure of YOLO.
Fig 8.
Comparison of YOLOv8 and old versions.
Fig 9.
Flowchart diagram of the proposed model.
Fig 10.
Ground station interface.
Fig 11.
Real-time flight detection test.
Fig 12.
Image processing workflow.
Fig 13.
Forest fire dataset.
Fig 14.
Evaluation matrix for CNN-RCNN.
Fig 15.
YOLOv8 vs YOLOv5 model training results.
Fig 16.
Training results of the YOLOv8 classification.
Table 4.
The confusion matrix resulting from proposed models.
Table 5.
Confusion matrix reports for proposed models.
Table 6.
Performance measurements of object detections for YOLOv5 VS YOLOv8.
Fig 17.
Real-time results for object detection.