An important application scenario for target detection is the detection and location of indoor mobile personnel. In this study, we propose an indoor personnel detection method to improve YOLOv3. First, the proposed method clusters the dataset by using K-means algorithm and designs a DE-YOLO deep convolutional neural network structure. Through the dense connection in the DE-YOLO network structure, the compression of the model sizes and the reuse of the feature information are realized. Finally, the target detection is performed on the extracted features. Experiments show that the application of the newly improved deep convolutional network has greatly improved application effect on VOC2012 datasets.