Few-Shot Object Counting With Dynamic Similarity-Aware in Latent Space-Reference-Cited by-同舟云学术

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Few-Shot Object Counting With Dynamic Similarity-Aware in Latent Space

Published:2024 Issue: Volume:62 Page:1-14
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

He Jinghui¹^ORCID,Liu Bo¹^ORCID,Cao Fan²^ORCID,Xu Jian²^ORCID,Xiao Yanshan³^ORCID

Affiliation:

1. School of Electro-Mechanical Engineering, Guangdong University of Technology, Guangzhou, China

2. School of Automation, Guangdong University of Technology, Guangzhou, China

3. School of Automation and the School of Computer Science, Guangdong University of Technology, Guangzhou, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10381743.pdf?arnumber=10381743

Reference59 articles.

1. U-Net: deep learning for cell counting, detection, and morphometry

2. Robust Hierarchical Deep Learning for Vehicular Management

3. Counting in the Wild

4. MACC Net: Multi-task attention crowd counting network

5. Single-Image Crowd Counting via Multi-Column Convolutional Neural Network

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