LSOD-YOLOv8: Enhancing YOLOv8n with New Detection Head and Lightweight Module for Efficient Cigarette Detection

LSOD-YOLOv8: Enhancing YOLOv8n with New Detection Head and Lightweight Module for Efficient Cigarette Detection

Cigarette detection is a crucial component of public safety management. However, detecting such small objects poses significant challenges due to their size and limited feature points. To enhance the accuracy of small target detection, we propose a novel small object detection model, LSOD-YOLOv8 (Li...

Full description

Saved in:
Bibliographic Details
Main Authors: Yijie Huang, Huimin Ouyang, Xiaodong Miao
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Applied Sciences
Subjects:
lightweight small object detection
pyramid pooling layer 2
shared convolutional
batch normalization
loss function
detection accuracy
Online Access:https://www.mdpi.com/2076-3417/15/7/3961
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2076-3417/15/7/3961

Similar Items