Object detection is extensively utilized in computer vision and is essential for various Applications, like self-driving cars. Over the past fifty years, object detection techniques have evolved significantly, leading to numerous innovative approaches with notable success. Today, object recognition methods primarily fall into two categories: traditional machine learning techniques and deep learning methods. This article reviews object detection techniques, first summarizing traditional machine learning-based methods. It then examines two prominent deep learning approaches, R-CNN and YOLO. Finally, the article compares and discusses the mentioned methods.