154 citations · 296 across the 21 of their papers we have counts for
21 papers
Hybrid Feature Embedding For Automatic Building Outline Extraction
Weihang Ran, Wei Yuan, Xiaodan Shi +2
Building outline extracted from high-resolution aerial images can be used in various application fields such as change detection and disaster assessment. However, traditional CNN m…
Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating the Impact of Spatial Resolution on Various Datasets
Zhiling Guo, Xiaodan Shi, Haoran Zhang +4
The development of remote sensing and deep learning techniques has enabled building semantic segmentation with high accuracy and efficiency. Despite their success in different task…
Metapopulation Graph Neural Networks: Deep Metapopulation Epidemic Modeling with Human Mobility
Qi Cao, Renhe Jiang, Chuang Yang +3
Epidemic prediction is a fundamental task for epidemic control and prevention. Many mechanistic models and deep learning models are built for this task. However, most mechanistic m…
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling
Zhiling Guo, Yinqiang Zheng, Haoran Zhang +4
In recent years, single-frame image super-resolution (SR) has become more realistic by considering the zooming effect and using real-world short- and long-focus image pairs. In thi…
Multitask Weakly Supervised Learning for Origin Destination Travel Time Estimation
Hongjun Wang, Zhiwen Zhang, Zipei Fan +4
Travel time estimation from GPS trips is of great importance to order duration, ridesharing, taxi dispatching, etc. However, the dense trajectory is not always available due to the…
GOF-TTE: Generative Online Federated Learning Framework for Travel Time Estimation
Zhiwen Zhang, Hongjun Wang, Jiyuan Chen +3
Estimating the travel time of a path is an essential topic for intelligent transportation systems. It serves as the foundation for real-world applications, such as traffic monitori…
Online Trajectory Prediction for Metropolitan Scale Mobility Digital Twin
Zipei Fan, Xiaojie Yang, Wei Yuan +4
Knowing "what is happening" and "what will happen" of the mobility in a city is the building block of a data-driven smart city system. In recent years, mobility digital twin that m…
Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
Zhiwen Zhang, Hongjun Wang, Zipei Fan +3
Due to the rapid development of Internet of Things (IoT) technologies, many online web apps (e.g., Google Map and Uber) estimate the travel time of trajectory data collected by mob…
Domain Adversarial Graph Convolutional Network Based on RSSI and Crowdsensing for Indoor Localization
Mingxin Zhang, Zipei Fan, Ryosuke Shibasaki +1
In recent years, the use of WiFi fingerprints for indoor positioning has grown in popularity, largely due to the widespread availability of WiFi and the proliferation of mobile com…
Event-Aware Multimodal Mobility Nowcasting
Zhaonan Wang, Renhe Jiang, Hao Xue +3
As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios…
Differentiable Projection for Constrained Deep Learning
Dou Huang, Haoran Zhang, Xuan Song +1
Deep neural networks (DNNs) have achieved extraordinary performance in solving different tasks in various fields. However, the conventional DNN model is steadily approaching the gr…
An open GPS trajectory dataset and benchmark for travel mode detection
Jinyu Chen, Haoran Zhang, Xuan Song +1
Travel mode detection has been a hot topic in the field of GPS trajectory-related processing. Former scholars have developed many mathematical methods to improve the accuracy of de…
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction
Renhe Jiang, Du Yin, Zhaonan Wang +7
Nowadays, with the rapid development of IoT (Internet of Things) and CPS (Cyber-Physical Systems) technologies, big spatiotemporal data are being generated from mobile phones, car…
Adapting Vehicle Detector to Target Domain by Adversarial Prediction Alignment
Yohei Koga, Hiroyuki Miyazaki, Ryosuke Shibasaki
While recent advancement of domain adaptation techniques is significant, most of methods only align a feature extractor and do not adapt a classifier to target domain, which would…
Effective Metagraph-based Life Pattern Clustering with Big Human Mobility Data
Wenjing Li, Haoran Zhang, Jinyu Chen +5
Life pattern clustering is essential for abstracting the groups' characteristics of daily mobility patterns and activity regularity. Based on millions of GPS records, this paper pr…
Mobsimilarity: Vector Graph Optimization for Mobility Tableau Comparison
Yuhao Yao, Haoran Zhang, Jinyu Chen +4
Human mobility similarity comparison plays a critical role in mobility estimation/prediction model evaluation, mobility clustering and mobility matching, which exerts an enormous i…
Deep-learning coupled with novel classification method to classify the urban environment of the developing world
Qianwei Cheng, AKM Mahbubur Rahman, Anis Sarker +6
Rapid globalization and the interdependence of humanity that engender tremendous in-flow of human migration towards the urban spaces. With advent of high definition satellite image…
EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control
Chuang Yang, Zhiwen Zhang, Zipei Fan +4
The outbreak of coronavirus disease (COVID-19) has swept across more than 180 countries and territories since late January 2020. As a worldwide emergency response, governments have…
VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
Renhe Jiang, Zekun Cai, Zhaonan Wang +5
Nowadays, massive urban human mobility data are being generated from mobile phones, car navigation systems, and traffic sensors. Predicting the density and flow of the crowd or tra…
Semantic Segmentation for Urban Planning Maps based on U-Net
Zhiling Guo, Hiroaki Shengoku, Guangming Wu +6
The automatic digitizing of paper maps is a significant and challenging task for both academia and industry. As an important procedure of map digitizing, the semantic segmentation…
Visual Graph Mining
Quanshi Zhang, Xuan Song, Ryosuke Shibasaki
In this study, we formulate the concept of "mining maximal-size frequent subgraphs" in the challenging domain of visual data (images and videos). In general, visual knowledge can u…