Titlebook: Spatial Data and Intelligence; First International Xiaofeng Meng,Xing Xie,Zhiming Ding Conference proceedings 2021 Springer Nature Switzer

政府

Attention U-Net for Road Extraction in Remote Sensing Imagesing in computer vision, automatic road extraction from remote sensing images is a research hotspot in recent years. However, due to the complicated image background and special road structure, the results of automatic road extraction are still far from perfect. In this paper, we propose a road segme

尖酸一点

College Students’ Portrait Technology Based on Hybrid Neural Networkis to gradually form a high-dimensional data storage system composed of student status information, educational administration information, behavior information, etc. It is of great significance to make use of the existing data of students in Colleges and universities to carry out deep-seated and pe

半球

AVOID

Efficiently Update Disk-Resident Interval Tree/O optimal method to efficiently update the disk-resident interval tree for a set of new intervals. The idea is to partition the input data into two parts and bulk-applies each part into the structure. Meanwhile, the tree balance is preserved. We introduce our proposal and develop alternative method

名字的误用

Performance Ranking Based on Bézier Ranking Principal Curveprincipal curve, and designs the learning algorithm of Bézier curve. First, evaluation indicators are chosen using Pearson correlation coefficient, RPC two-dimensional projection is conducted on relevant data and the ranking result of multiple indicator observation data is obtained. The experiment i

chalice

Detonate

Peristalsis

0302-9743 d on May 8-9, 2020. The conference was planned to take place in Shenzhen, China, and changed to an online format due to the COVID-19 pandemic. ..The 21 full papers presented in this volume were carefully reviewed and selected from 50 submissions. They were organized in topical sections named: traffi

Mundane

Dynamic Shortest Path Queries over Moving Objects on Road Networksments) of Nanjing, including the setting of the pre-stored coefficient ., the pre-stored path size, and the road network size. The results show that the MOSP algorithm proposed in this paper outperforms baseline approaches by 2–3 orders of magnitude.

diathermy

Fast Training of POI Recommendation Models Using Gradient Compressionof data transfer. Meanwhile, it modifies the Adam optimizer with an error feedback mechanism to avoid the decrease of POI recommendation accuracy resulting from gradient compression. Experimental results show that our methods can achieve similar even better accuracy than uncompressed methods while the communication time is shorter.