The task of object detection is to identify accurately,effectively loc ate the target object in the image,and predefine its category.Aiming at the problems that the SSD (singal shot multibox detector) object detection algorithm is not enough in detection accurac y and efficiency in small object detection,an improved SSD algorithm based on space-channel att ention SC_SSD (spatial and channel singal shot multibox detector) is proposed.By introducing the space-channel attention mechanism into SSD deep network,the semantic informati on of high-level feature can be enhanced,and the algorithm is capable of capturing t he information of details and position of the target object.As a result,the rates of missed dete ction and false detection are reduced and the detection accuracy for small object is improved.I n addition,the deep separable convolution in MobileNetV2is used to prune the SSD backbone netw ork VGG-16(visual geometry group network).This will reduce the number of parameter s and will improve efficiency of training and detection.Experiments on Pascal VOC2007data set show that the detection precision and the detection rate of the proposed algorithm is 78.9% and 59.4Fps, respectively,3.2% and 26.7Fps higher than SSD algorithm,meeting the real-tim e requirements. The proposed algorithm is also superior to that of the previous ones and is an e ffective and feasible object detection algorithm.