In this study, we apply the energy model to improve accuracy and performance in object detection. The research uses popular datasets such as PASCAL VOC 2012 to train and evaluate the model. The results show that by integrating energy models instead of relying solely on regression methods to predict the bounding box coordinates, as in traditional approaches, this energy-based framework combines visual, geometric, and spatial factors to optimize object detection more comprehensively and accurately.