Search Results for author: Hao Sheng

Found 18 papers, 3 papers with code

Detecting Neighborhood Gentrification at Scale via Street-level Visual Data

no code implementations4 Jan 2023 Tianyuan Huang, Timothy Dai, Zhecheng Wang, Hesu Yoon, Hao Sheng, Andrew Y. Ng, Ram Rajagopal, Jackelyn Hwang

Neighborhood gentrification plays a significant role in shaping the social and economic well-being of both individuals and communities at large.


Extracting Built Environment Features for Planning Research with Computer Vision: A Review and Discussion of State-of-the-Art Approaches

no code implementations30 Jan 2022 Meiqing Li, Hao Sheng

This is an extended abstract for a presentation at The 17th International Conference on CUPUM - Computational Urban Planning and Urban Management in June 2021.


Probability Paths and the Structure of Predictions over Time

1 code implementation NeurIPS 2021 Zhiyuan Jerry Lin, Hao Sheng, Sharad Goel

Given a collection of such probability paths, we introduce a Bayesian framework -- which we call the Gaussian latent information martingale, or GLIM -- for modeling the structure of dynamic predictions over time.

Time Series Analysis

Learning Neighborhood Representation from Multi-Modal Multi-Graph: Image, Text, Mobility Graph and Beyond

no code implementations6 May 2021 Tianyuan Huang, Zhecheng Wang, Hao Sheng, Andrew Y. Ng, Ram Rajagopal

Recent urbanization has coincided with the enrichment of geotagged data, such as street view and point-of-interest (POI).

Surveilling Surveillance: Estimating the Prevalence of Surveillance Cameras with Street View Data

no code implementations4 May 2021 Hao Sheng, Keniel Yao, Sharad Goel

In a detailed analysis of the 10 U. S. cities, we find that cameras are concentrated in commercial, industrial, and mixed zones, and in neighborhoods with higher shares of non-white residents -- a pattern that persists even after adjusting for land use.

Face Recognition

Multi-Task Time Series Forecasting With Shared Attention

no code implementations24 Jan 2021 Zekai Chen, Jiaze E, Xiao Zhang, Hao Sheng, Xiuzheng Cheng

Time series forecasting is a key component in many industrial and business decision processes and recurrent neural network (RNN) based models have achieved impressive progress on various time series forecasting tasks.

Time Series Time Series Forecasting

A General Recurrent Tracking Framework Without Real Data

no code implementations ICCV 2021 Shuai Wang, Hao Sheng, Yang Zhang, Yubin Wu, Zhang Xiong

Based on this framework, a Recurrent Tracking Unit (RTU) is designed to score potential tracks through long-term information.

Multi-Object Tracking

AGenT Zero: Zero-shot Automatic Multiple-Choice Question Generation for Skill Assessments

no code implementations25 Nov 2020 Eric Li, Jingyi Su, Hao Sheng, Lawrence Wai

Multiple-choice questions (MCQs) offer the most promising avenue for skill evaluation in the era of virtual education and job recruiting, where traditional performance-based alternatives such as projects and essays have become less viable, and grading resources are constrained.

Multiple-choice Question Generation +3

A Distributed Privacy-Preserving Learning Dynamics in General Social Networks

no code implementations15 Nov 2020 Youming Tao, Shuzhen Chen, Feng Li, Dongxiao Yu, Jiguo Yu, Hao Sheng

In this paper, we study a distributed privacy-preserving learning problem in social networks with general topology.

Privacy Preserving

OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery

no code implementations14 Nov 2020 Hao Sheng, Jeremy Irvin, Sasankh Munukutla, Shawn Zhang, Christopher Cross, Kyle Story, Rose Rustowicz, Cooper Elsworth, Zutao Yang, Mark Omara, Ritesh Gautam, Robert B. Jackson, Andrew Y. Ng

In this work, we develop deep learning algorithms that leverage freely available high-resolution aerial imagery to automatically detect oil and gas infrastructure, one of the largest contributors to global methane emissions.


ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery

1 code implementation11 Nov 2020 Jeremy Irvin, Hao Sheng, Neel Ramachandran, Sonja Johnson-Yu, Sharon Zhou, Kyle Story, Rose Rustowicz, Cooper Elsworth, Kemen Austin, Andrew Y. Ng

Characterizing the processes leading to deforestation is critical to the development and implementation of targeted forest conservation and management policies.

General Classification Management

A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables

no code implementations27 Oct 2020 Xiaoting Wang, Xiaozhe Wang, Hao Sheng, Xi Lin

The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC).

Computational Efficiency

Effective Data Fusion with Generalized Vegetation Index: Evidence from Land Cover Segmentation in Agriculture

no code implementations7 May 2020 Hao Sheng, Xiao Chen, Jingyi Su, Ram Rajagopal, Andrew Ng

How can we effectively leverage the domain knowledge from remote sensing to better segment agriculture land cover from satellite images?

PIV-Based 3D Fluid Flow Reconstruction Using Light Field Camera

no code implementations15 Apr 2019 Zhong Li, Jinwei Ye, Yu Ji, Hao Sheng, Jingyi Yu

Particle Imaging Velocimetry (PIV) estimates the flow of fluid by analyzing the motion of injected particles.

Depth Estimation Optical Flow Estimation

Generic Multiview Visual Tracking

no code implementations4 Apr 2019 Minye Wu, Haibin Ling, Ning Bi, Shenghua Gao, Hao Sheng, Jingyi Yu

A natural solution to these challenges is to use multiple cameras with multiview inputs, though existing systems are mostly limited to specific targets (e. g. human), static cameras, and/or camera calibration.

Camera Calibration Trajectory Prediction +1

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