Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges
The COVID-19 pandemic poses unprecedented challenges around the world. Many studies
have applied mobility data to explore spatiotemporal trends over time, investigate …
have applied mobility data to explore spatiotemporal trends over time, investigate …
State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Classification of remote sensing images using EfficientNet-B3 CNN model with attention
Scene classification is a highly useful task in Remote Sensing (RS) applications. Many
efforts have been made to improve the accuracy of RS scene classification. Scene …
efforts have been made to improve the accuracy of RS scene classification. Scene …
[HTML][HTML] Information retrieval meets large language models: a strategic report from chinese ir community
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond
traditional search to meet diverse user information needs. Recently, Large Language …
traditional search to meet diverse user information needs. Recently, Large Language …
Predicting urban region heat via learning arrive-stay-leave behaviors of private cars
Urban region heat refers to the extent of which people congregate in various regions when
they travel to and stay in a specified place. Predicting urban region heat facilitates broad …
they travel to and stay in a specified place. Predicting urban region heat facilitates broad …
[HTML][HTML] Machine learning for spatial analyses in urban areas: a scoping review
The challenges for sustainable cities to protect the environment, ensure economic growth,
and maintain social justice have been widely recognized. Along with the digitization …
and maintain social justice have been widely recognized. Along with the digitization …
Trajectory data mining: an overview
Y Zheng - ACM Transactions on Intelligent Systems and …, 2015 - dl.acm.org
The advances in location-acquisition and mobile computing techniques have generated
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …
massive spatial trajectory data, which represent the mobility of a diversity of moving objects …
Extracting urban functional regions from points of interest and human activities on location‐based social networks
Data about points of interest (POI) have been widely used in studying urban land use types
and for sensing human behavior. However, it is difficult to quantify the correct mix or the …
and for sensing human behavior. However, it is difficult to quantify the correct mix or the …
Sensing spatial distribution of urban land use by integrating points-of-interest and Google Word2Vec model
Urban land use information plays an essential role in a wide variety of urban planning and
environmental monitoring processes. During the past few decades, with the rapid …
environmental monitoring processes. During the past few decades, with the rapid …