Deep Learning In Military Object Detection: An Example of The Yolo-Nas Model

Deep learning plays a crucial role in military object detection, a critical aspect of military operations. Specifically, the You Only Look Once (YOLO) object detection algorithm is highly significant, allowing the simultaneous detection of multiple objects, thereby enhancing efficiency in military operations. Various versions of YOLO, such as YOLOv5s, YOLOv51, YOLOv7, and YOLOv8, have been developed to provide significant improvements in object detection. For instance, the YOLO-NAS-S model, according to the analysis results, has demonstrated the highest performance. With impressive results like $\mathbf{98.4 \%}$ accuracy, $\mathbf{97.6 \%}$ precision, and $\mathbf{97.2 \%}$ recall, it has proven to be a preferred option. These outcomes underscore the importance of deep learning in achieving fast and accurate results. Future studies aim to provide more advanced solutions in military object detection, enabling the use of more effective and reliable methods in military operations. The continuous advancement of deep learning technology will play a crucial role in increasing security and success rates in military operations.