(untitled) (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Artificial Intelligence is taking part in many forms of daily human life. Many innovations have been embedded in technology to ensure they reach the same or even higher than human capability. One of the trending innovations in the market is image recognition. Image recognition is now implementing machine learning and deep learning for better image detection. Usual issues come for any image recognition technology about the low ability to detect various object classes. Too much research on image recognition also led to difficulty in applying the best algorithms. Although there are many technologies regarding image recognition, there is still not much work on human pose detection. Therefore, this paper proposed an application for detecting human pose related to drone control using a deep learning algorithm. This research aims to review the type of deep learning algorithm for human pose detection, develop an enhanced algorithm based on deep learning algorithm for human pose classification, and evaluate the proposed human pose classification algorithm’s performance based on accuracy using drone technology. This paper proposes using Convolutional Neural Network (CNN) as a selected deep learning algorithm suitable for pattern recognition. This research expects an accurate result for detecting the human pose involving controlling the drone.