22 citations · 62 across the 11 of their papers we have counts for
6 papers · 1 filter
Rethinking Mobile Block for Efficient Attention-based Models
Jiangning Zhang, Xiangtai Li, Jian Li +7
This paper focuses on developing modern, efficient, lightweight models for dense predictions while trading off parameters, FLOPs, and performance. Inverted Residual Block (IRB) ser…
ClickTrain: Efficient and Accurate End-to-End Deep Learning Training via Fine-Grained Architecture-Preserving Pruning
Chengming Zhang, Geng Yuan, Wei Niu +8
Convolutional neural networks (CNNs) are becoming increasingly deeper, wider, and non-linear because of the growing demand on prediction accuracy and analysis quality. The wide and…
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…
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…
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…
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…