A deep learning framework for object detection under rainy conditions
Adhesive raindrops on glass have been known to diffract light and distort parts of the scene behind them. In the modern days object detection applications, these raindrops pose as a nuisance since they hamper the detectability of the objects in a scene. As a result, much more effort has been placed...
Saved in:
Main Author: | Tay, Nicholas Kwang Wei |
---|---|
Other Authors: | Soong Boon Hee |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139580 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Deep learning for object detection under rainy conditions
by: Chin, Zhuo Sheng
Published: (2018) -
Generative Adversarial Networks (GANs) for object detection under rainy conditions
by: Teo, Oliver Kwok Rong
Published: (2020) -
Multimodal data fusion for object detection under rainy conditions
by: Liu, Ting Tao
Published: (2022) -
Adaptation of object detection networks under anomalous conditions
by: Koh, Rachel
Published: (2023) -
Lane perception in rainy conditions for autonomous vehicles
by: Mahendran, Prabhu Shankar
Published: (2024)