Light-YOLOv5: A Lightweight Algorithm for Improved YOLOv5 in Complex Fire Scenarios
Fire-detection technology is of great importance for successful fire-prevention measures. Image-based fire detection is one effective method. At present, object-detection algorithms are deficient in performing detection speed and accuracy tasks when they are applied in complex fire scenarios. In thi...
Main Authors: | Hao Xu, Bo Li, Fei Zhong |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2022-12-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/12/23/12312 |
Similar Items
-
Lightweight Apple Detection in Complex Orchards Using YOLOV5-PRE
by: Lijuan Sun, et al.
Published: (2022-12-01) -
An improved lightweight object detection algorithm for YOLOv5
by: Hao Luo, et al.
Published: (2024-01-01) -
Lightweight Algorithm for Apple Detection Based on an Improved YOLOv5 Model
by: Yu Sun, et al.
Published: (2023-08-01) -
Ship Detection Algorithm Based on YOLOv5 Network Improved with Lightweight Convolution and Attention Mechanism
by: Langyu Wang, et al.
Published: (2023-11-01) -
YOLOv5-Sewer: Lightweight Sewer Defect Detection Model
by: Xingliang Zhao, et al.
Published: (2024-02-01)