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20192022
most citedDynamic Image for 3D MRI Image Alzheimer's Disease Classification

34 citations · 35 across the 5 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CV2020

A Structure-Aware Method for Direct Pose Estimation

Hunter Blanton, Scott Workman, Nathan Jacobs

Estimating camera pose from a single image is a fundamental problem in computer vision. Existing methods for solving this task fall into two distinct categories, which we refer to…

cs.CV2020★ 34 cited

Dynamic Image for 3D MRI Image Alzheimer's Disease Classification

Xin Xing, Gongbo Liang, Hunter Blanton +4

We propose to apply a 2D CNN architecture to 3D MRI image Alzheimer's disease classification. Training a 3D convolutional neural network (CNN) is time-consuming and computationally…

cs.CV2020

Single Image Cloud Detection via Multi-Image Fusion

Scott Workman, M. Usman Rafique, Hunter Blanton +2

Artifacts in imagery captured by remote sensing, such as clouds, snow, and shadows, present challenges for various tasks, including semantic segmentation and object detection. A pr…

cs.CV2020

RasterNet: Modeling Free-Flow Speed using LiDAR and Overhead Imagery

Armin Hadzic, Hunter Blanton, Weilian Song +3

Roadway free-flow speed captures the typical vehicle speed in low traffic conditions. Modeling free-flow speed is an important problem in transportation engineering with applicatio…

cs.CV2020

Joint 2D-3D Breast Cancer Classification

Gongbo Liang, Xiaoqin Wang, Yu Zhang +4

Breast cancer is the malignant tumor that causes the highest number of cancer deaths in females. Digital mammograms (DM or 2D mammogram) and digital breast tomosynthesis (DBT or 3D…

cs.CV2020

2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification

Yu Zhang, Xiaoqin Wang, Hunter Blanton +3

Automated methods for breast cancer detection have focused on 2D mammography and have largely ignored 3D digital breast tomosynthesis (DBT), which is frequently used in clinical pr…