Performance Validation of Yolo Variants for Object Detection-Reference-Cited by-同舟云学术

Performance Validation of Yolo Variants for Object Detection

Published:2021-01-22 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing
language:
Short-container-title:

Author:

Liu Kaiyue¹,Tang Haitong¹,He Shuang¹,Yu Qin²,Xiong Yulong²,Wang Nizhuan¹

Affiliation:

1. Artificial Intelligence & Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, Jiangsu, China and School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang, Jiangsu, China

2. Artificial Intelligence & Neuro-Informatics Engineering (ARINE) Laboratory, School of Computer Engineering, Jiangsu Ocean University, Lianyungang, Jiangsu, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3448748.3448786

Reference13 articles.

1. Girshick R. Fast r-cnn[C]//Proceedings of the IEEE international conference on computer vision. 2015: 1440--1448. Girshick R. Fast r-cnn[C]//Proceedings of the IEEE international conference on computer vision. 2015: 1440--1448.

2. Comparison of Faster-RCNN, YOLO, and SSD for Real-Time Vehicle Type Recognition[C]//2020 IEEE International Conference on Consumer Electronics-Asia (ICCE-Asia);Kim J;IEEE

3. Comparison of object detection algorithms using adaptive background models[C]//2005 IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance;Hall D;IEEE

4. Redmon J Divvala S Girshick R etal You only look once: Unified real-time object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779--788. Redmon J Divvala S Girshick R et al. You only look once: Unified real-time object detection[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 779--788.

Cited by 39 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. RPH-Counter: Field detection and counting of rice planthoppers using a fully convolutional network with object-level supervision;Computers and Electronics in Agriculture;2024-10

2. Automatic Face Detection of Farm Images Based on an Enhanced Lightweight Deep Learning Model;International Journal of Pattern Recognition and Artificial Intelligence;2024-08-21

3. Evaluation of YOLOv8 Model Series with HOP for Object Detection in Complex Agriculture Domains;International Journal of Pure and Applied Sciences;2024-06-30

4. Turning Features Detection from Aerial Images: Model Development and Application on Florida’s Public Roadways;Smart Cities;2024-06-13

5. Design and Testing of an Autonomous Navigation Unmanned Surface Vehicle for Buoy Inspection;Journal of Marine Science and Engineering;2024-05-14