Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"

Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"，specifically included are water content data from 55 in situ observations for the years 2018-2020 (observation frequency of 5min or 10min), and example code for implementing LSTM and PCDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research</p

Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"

Data and code used in the article "A deep learning method for predicting soil moisture in unsaturated areas based on physical constraints"，specifically included are water content data from 55 in situ observations for the years 2018-2020 (observation frequency of 5min or 10min), and example code for implementing LSTM and PCDL using python (mainly the tensorflow library).These data can help the reader to better understand and replicate our research</p

Lane marking image-CMU

The image set is download from the website of vasc lab in Carnegie Mellon University, so the copyright of the image set belongs to Carnegie Mellon University . The image set contain 160 lane marking images. The image size is 256*240, image format is png

360+x : A Panoptic Multi-modal Scene Understanding Dataset

60+x dataset introduces a unique panoptic perspective to scene understanding, differentiating itself from existing datasets, by offering multiple viewpoints and modalities, captured from a variety of scenes. Our dataset contains: 1. 2,152 multi-model videos captured by 360° cameras and Spectacles cameras (8,579k frames in total) 2. Capture in 17 cities across 5 countries. 3. Capture in 28 Scenes from Artistic Spaces to Natural Landscapes. 4. Temporal Activity Localisation Labels for 38 action instances for each video. IMPORTANT NOTICE: Due to the large volume of the data files, they have been stored in the BEAR Research Data Store space. If you wish to access the data, please contact [email protected] to request and receive the relevant link to the data folder

sj-docx-1-wso-10.1177_17474930221109149 – Supplemental material for Efficacy and safety of vitamin-K antagonists and direct oral anticoagulants for stroke prevention in patients with heart failure and sinus rhythm: An updated systematic review and meta-analysis of randomized clinical trials

Supplemental material, sj-docx-1-wso-10.1177_17474930221109149 for Efficacy and safety of vitamin-K antagonists and direct oral anticoagulants for stroke prevention in patients with heart failure and sinus rhythm: An updated systematic review and meta-analysis of randomized clinical trials by Weijia Li, Jiyoung Seo, Damianos G Kokkinidis, Leonidas Palaiodimos, Sanjana Nagraj, Eleni Korompoki, Haralambos Milionis, Wolfram Doehner, Gregory Y. H. Lip and George Ntaios in International Journal of Strok