Cargando…
Mixed YOLOv3-LITE: A Lightweight Real-Time Object Detection Method
Embedded and mobile smart devices face problems related to limited computing power and excessive power consumption. To address these problems, we propose Mixed YOLOv3-LITE, a lightweight real-time object detection network that can be used with non-graphics processing unit (GPU) and mobile devices. B...
Autores principales: | Zhao, Haipeng, Zhou, Yang, Zhang, Long, Peng, Yangzhao, Hu, Xiaofei, Peng, Haojie, Cai, Xinyue |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180807/ https://www.ncbi.nlm.nih.gov/pubmed/32230867 http://dx.doi.org/10.3390/s20071861 |
Ejemplares similares
-
SenseLite: A YOLO-Based Lightweight Model for Small Object Detection in Aerial Imagery
por: Han, Tianxin, et al.
Publicado: (2023) -
Lightweight aerial image object detection algorithm based on improved YOLOv5s
por: Deng, Lixia, et al.
Publicado: (2023) -
LPO-YOLOv5s: A Lightweight Pouring Robot Object Detection Algorithm
por: Zhao, Kanghui, et al.
Publicado: (2023) -
A Lightweight and Accurate UAV Detection Method Based on YOLOv4
por: Cai, Hao, et al.
Publicado: (2022) -
Lightweight Model for Pavement Defect Detection Based on Improved YOLOv7
por: Huang, Peile, et al.
Publicado: (2023)