Subject
- Biomedical Engineering 8
- Mechanical Engineering 2
- Computer Science 1
- Interdisciplinary Research 1
- Life Sciences 1
Creator
- Haiguang Wen 7
- Junxing Shi 7
- Zhongming Liu, 0000-0002-8773-4204 7
- Jiayue Cao 6
- Kun-Han Lu, 0000-0002-0355-8515 6
- Yizhen Zhang 6
- Nina Mahmoudian, 0000-0002-3285-8234 2
- Zihan Wang 2
- Amir Hossein Raffiee 1
- Arezoo M. Ardekani 1
Type
- Dataset 14
Date
subject: deep learning type: dataset
Total is 14 Results
River Obstacle Segmentation En-route By USV Dataset (ROSEBUD)
10.4231/MMJ2-NH88
Jalil Francisco Chavez Galaviz
,
Jianwen Li
,
Nina Mahmoudian
,
Reeve David Lambert
,
Zihan Wang
06/12/2022
This dataset contains stills from video taken on Sugar Creek and the Wabash River in the US state of Indiana. Images are hand annotated to provide training and testing data for semantic segmentation networks.
autonomous and connected vehicles deep learning Mechanical Engineering River Robotics semantic segmentation
Aerial Fluvial Image Dataset (AFID) for Semantic Segmentation
10.4231/B129-XD47
Li-Fan Wu
,
Nina Mahmoudian
,
Zihan Wang
07/20/2022
816 2K/2.7K per-pixel annotated images with 8 classes: River, Boat, Bridge, Sky, Forest vegetation, Dry sediment, Drone self and Obstacle in river. Fluvial scenes are from Wabash River and Wildcat Creek in Indiana, USA.
Artificial Neural Network (ANN) autonomos vehicles Collision Avoidance deep learning drone Image Dataset Mechanical Engineering navigation RGB image dataset River Robotics semantic segmentation Unmanned Aerial Vehicle Wabash River
Raw Data and Results from Automatic Murine Cardiac Ultrasound and Photoacoustic Image Segmentations
10.4231/9C8X-H052
Craig J Goergen
,
Hayley Chan
,
Katherine Leyba
,
Olivia Claire Loesch
,
Pierre Sicard
05/25/2023
Accuracy and dice scores from cross-validation reported in the cross-validation results spreadsheet. Radial strain raw data and results reported in strain results spreadsheet. Oxygen saturation values reported in sO2 results spreadsheet.
cardiovascular deep learning Imaging photoacoustic imaging ultrasound
A deep learning neural network to extract of P- and S-wave transit times from Vertical Seismic Profile (VSP)
10.4231/TT0F-KH40
Douglas R Schmitt
,
Oumeng Zhang
07/23/2024
This archive contains the training dataset and the Python code to train a deep learning neural net that aims to extract separately P and S wave arrival transit times from synthetic common shot gathers (CSG) in a deviated borehole geometry.
deep learning Machine Learning Machine Learning and Geophysical Signals seismic behavior
Display #
Results 1 - 10 of 14