Self-supervised learning for hotspot detection and isolation from thermal images
Hotspot detection using thermal imaging has recently become essential in several industrial applications, such as security applications that require identification of suspicious activities or intruders by detecting hotspots generated by human body heat, health applications such as screening of indiv...
Saved in:
Main Authors: | Goyal, Shreyas, Rajapakse, Jagath Chandana |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/170901 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Thermal image analytics for industrial anomaly detection
by: Goyal, Shreyas
Published: (2024) -
Unraveling the ‘anomaly’ in time series anomaly detection: A self-supervised tri-domain solution
by: SUN, Yuting, et al.
Published: (2024) -
Self-supervised feature learning for semantic segmentation of overhead imagery
by: SINGH, Suriya, et al.
Published: (2018) -
SELF-SUPERVISED DEEP LEARNING FOR IMAGE DENOISING AND BEYOND
by: ZHENG HUAN
Published: (2024) -
SELF-SUPERVISED MODELING FOR MULTI-MODAL UNDERSTANDING
by: YUE XIANGHU
Published: (2024)