RGB-T Object Detection With Failure Scenarios
Currently, RGB-thermal (RGB-T) object detection algorithms have demonstrated excellent performance, but issues such as modality failure caused by fog, strong light, sensor damage, and other conditions can significantly impact the detector's performance. This article proposes a multimodal...
Saved in:
Main Authors: | Qingwang Wang, Yuxuan Sun, Yongke Chi, Tao Shen |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10817087/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Broadband Normalized Difference Reflectance Indices and the Normalized Red–Green Index as a Measure of Drought in Wheat and Pea Plants
by: Ekaterina Sukhova, et al.
Published: (2024-12-01) -
RGB Approach for Pixel-Wise Identification of Cellulose Nitrate Photo Negative Yellowing
by: Anastasia Povolotckaia, et al.
Published: (2025-01-01) -
NDVI Estimation Throughout the Whole Growth Period of Multi-Crops Using RGB Images and Deep Learning
by: Jianliang Wang, et al.
Published: (2024-12-01) -
Tampered text detection via RGB and frequency relationship modeling
by: Yuxin WANG, et al.
Published: (2022-06-01) -
Optimizing colorectal polyp detection and localization: Impact of RGB color adjustment on CNN performance
by: Jirakorn Jamrasnarodom, et al.
Published: (2025-06-01)