CT-Net: An Efficient Network for Low-Altitude Object Detection Based on Convolution and Transformer-Reference-Cited by-同舟云学术

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CT-Net: An Efficient Network for Low-Altitude Object Detection Based on Convolution and Transformer

Published:2022 Issue: Volume:71 Page:1-12
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Ye Tao¹^ORCID,Zhang Jun¹^ORCID,Li Yunwang¹^ORCID,Zhang Xi¹^ORCID,Zhao Zongyang¹^ORCID,Li Zezhong¹^ORCID

Affiliation:

1. School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China

Funder

Foundation of the State Key Laboratory of Coal Mining and Clean Utilization, China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/9717300/09751710.pdf?arnumber=9751710

Reference43 articles.

1. YOLOv4: Optimal speed and accuracy of object detection;bochkovskiy;arXiv 2004 10934,2020

2. Learning spatial fusion for single-shot object detection;liu;arXiv 1911 09516,2019

3. Feature pyramid network for object detection;lin;Proc Comput Vis Pattern Recognit,2016

4. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc JMLR,2015

5. Instance normalization: The missing ingredient for fast stylization;ulyanov;arXiv 1607 08022,2016

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