activity
20182020
most citedDeep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy

1 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV20201 cited

Deep Learning for Earth Image Segmentation based on Imperfect Polyline Labels with Annotation Errors

Zhe Jiang, Marcus Stephen Kirby, Wenchong He +1

In recent years, deep learning techniques (e.g., U-Net, DeepLab) have achieved tremendous success in image segmentation. The performance of these models heavily relies on high-qual…

cs.LG2020

Spatial Classification With Limited Observations Based On Physics-Aware Structural Constraint

Arpan Man Sainju, Wenchong He, Zhe Jiang +2

Spatial classification with limited feature observations has been a challenging problem in machine learning. The problem exists in applications where only a subset of sensors are d…

cs.CV20201 cited

Deep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy

Wenchong He, Arpan Man Sainju, Zhe Jiang +1

Given a 3D surface defined by an elevation function on a 2D grid as well as non-spatial features observed at each pixel, the problem of surface segmentation aims to classify pixels…

cs.CV2020

Flood Extent Mapping based on High Resolution Aerial Imagery and DEM: A Hidden Markov Tree Approach

Zhe Jiang, Arpan Man Sainju

Flood extent mapping plays a crucial role in disaster management and national water forecasting. In recent years, high-resolution optical imagery becomes increasingly available wit…

cs.CV2019

Mapping road safety features from streetview imagery: A deep learning approach

Arpan Sainju, Zhe Jiang

Each year, around 6 million car accidents occur in the U.S. on average. Road safety features (e.g., concrete barriers, metal crash barriers, rumble strips) play an important role i…

cs.LG2018

Geographical Hidden Markov Tree for Flood Extent Mapping (With Proof Appendix)

Miao Xie, Zhe Jiang, Arpan Man Sainju

Flood extent mapping plays a crucial role in disaster management and national water forecasting. Unfortunately, traditional classification methods are often hampered by the existen…