Analysis of Computer Vision Application in The Context of SAR Missions

This work includes a general feasibility and performance analysis of some image classification models for Search And Rescue (SAR) operations. Since SAR missions are typically high-wear and high-risk situations for both the victims and the SAR crew, some teams around the globe have been seeking to use technology to speed up rescues and reduce damages. The Croatian Mountain Rescue Service (CMRS) and other SAR teams have been using Unmanned Aerial Systems (UAS) to obtain bird’s eye captures of the search area, contrasting with typical low-altitude manned flies. This paper uses the HERIDAL dataset images to train, validate, and test models. We used two different neural network architectures and eight different training parameters. Accuracy above 98% was achieved, but it doesn’t necessarily mean that the models are appropriate for real-life use, so several considerations were made. Keywords— Artificial Intelligence and Machine Learning. Search and Rescue (SAR) Missions. Performance Analysis