activity
20142020
most citedDAPnet: A Double Self-attention Convolutional Network for Point Cloud Semantic Labeling

15 citations · 32 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2020★ 15 cited

DAPnet: A Double Self-attention Convolutional Network for Point Cloud Semantic Labeling

Li Chen, Zewei Xu, Yongjian Fu +3

Airborne Laser Scanning (ALS) point clouds have complex structures, and their 3D semantic labeling has been a challenging task. It has three problems: (1) the difficulty of classif…

cs.DC2017

MovePattern: Interactive Framework to Provide Scalable Visualization of Movement Patterns

Kiumars Soltani, Anand Padmanabhan, Shaowen Wang

The rapid growth of movement data sources such as GPS traces, traffic networks and social media have provided analysts with the opportunity to explore collective patterns of geogra…

cs.SI2017

Depicting urban boundaries from a mobility network of spatial interactions: A case study of Great Britain with geo-located Twitter data

Junjun Yin, Aiman Soliman, Dandong Yin +1

Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. Defining urban boundaries that consider socio-economic re…

cs.SI2016★ 1 cited

Consistency of Social Sensing Signatures Across Major US Cities

Aiman Soliman, Kiumars Soltani, Anand Padmanabhan +1

Previous studies have shown that Twitter users have biases to tweet from certain locations, locational bias, and during certain hours, temporal bias. We used three years of geoloca…

cs.SI2015★ 4 cited

Where Chicagoans tweet the most: Semantic analysis of preferential return locations of Twitter users

Aiman Soliman, Junjun Yin, Kiumars Soltani +2

Recent studies on human mobility show that human movements are not random and tend to be clustered. In this connection, the movements of Twitter users captured by geo-located tweet…

cs.SI2015★ 4 cited

Urban spatial-temporal activity structures: a New Approach to Inferring the Intra-urban Functional Regions via Social Media Check-In Data

Ye Zhi, Yu Liu, Shaowen Wang +3

Most existing literature focuses on the exterior temporal rhythm of human movement to infer the functional regions in a city, but they neglects the underlying interdependence betwe…

cs.SI2014★ 8 cited

A Scalable Framework for Spatiotemporal Analysis of Location-based Social Media Data

Guofeng Cao, Shaowen Wang, Myunghwa Hwang +3

In the past several years, social media (e.g., Twitter and Facebook) has been experiencing a spectacular rise and popularity, and becoming a ubiquitous discourse for content sharin…