Intelligent Sensors for POI Recommendation Model Using Deep Learning in Location-Based Social Network Big Data.

Aiming at the problem that the existing Point of Interest (POI) recommendation model in social network big data is difficult to extract deep feature information, a POI recommendation model based on deep learning in social networks and big data is proposed in this article. The input data are all gathered through intelligent sensors to apply some raw data pre-processing tasks and thus reduce the computational burden on the model. First, a POI static feature extraction method based on symmetric matrix decomposition is designed to capture the geographical location and POI category features in Location-Based Social Networking (LBSN).

A Multiperson Pose Estimation Method Using Depthwise Separable Convolutions and Feature Pyramid Network.

In the process of multiperson pose estimation, there are problems such as slow detection speed, low detection accuracy of key point targets, and inaccurate positioning of the boundaries of people with serious occlusion. A multiperson pose estimation method using depthwise separable convolutions and feature pyramid network is proposed. Firstly, the YOLOv3 target detection algorithm model based on the depthwise separable convolution is used to improve the running speed of the human body detector.

A treatment option for severe cerebellar hemorrhage with ventricular extension in elderly patients: intraventricular fibrinolysis.

External ventricular drainage (EVD) combined with intraventricular fibrinolysis (IVF) is rarely used in severe spontaneous cerebellar hemorrhage (SCH) with intraventricular hemorrhage (IVH). Recently, the treatment strategy was repeatedly performed in our hospital to elderly patients with severe SCH + IVH. To analyze its clinical value, we compared it to two treatment strategies which now commonly are used for these patients: conservative management (CM) and clot evacuation (CE).