Name
Title | ||
|---|---|---|
Understanding Deformation Motion of Colloidal Nanosheets from CLSM Images using Deep Learning-based Approach |
Abstract | ||
|---|---|---|
This paper considers a problem of understanding deformation motion of colloidal nanosheets from a set of confocal laser scanning microscopy (CLSM) images corrupted by noises. First, we present a robust method for detecting nanosheet objects from noisy CLSM images by introducing the deep learning-based approach. Then, we develop a method for understanding motions of nanosheet objects in colloid liquid. Such a method is constituted by introducing the idea of the so-called gradient-based feature descriptor, in which the local and global deformation motions are effectively visualized. The performance is demonstrated by some experimental studies. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ICARCV.2018.8581084 | 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) |
Keywords | Field | DocType |
colloidal nanosheets,deep learning-based approach,confocal laser scanning microscopy images,nanosheet objects,noisy CLSM images,colloid liquid,local deformation motions,global deformation motions,gradient-based feature descriptor | Computer vision,Feature descriptor,Computer science,Control engineering,Colloid,Artificial intelligence,Deformation (mechanics),Deep learning,Nanosheet,Confocal laser scanning microscopy | Conference |
ISSN | ISBN | Citations |
2474-2953 | 978-1-5386-9583-8 | 0 |
PageRank | References | Authors |
0.34 | 1 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hiroyuki Fujioka | 1 | 37 | 13.37 |
| Jarupat Sawangphol | 2 | 0 | 0.34 |
| Shinya Anraku | 3 | 0 | 0.34 |
| Nobuyoshi Miyamoto | 4 | 0 | 0.68 |
| Akinori Hidaka | 5 | 52 | 8.08 |
| Hiroyuki Kano | 6 | 75 | 19.05 |