Few shot object detection for headdresses and seats in Thangka Yidam based on ResNet and deformable convolution-Reference-Cited by-同舟云学术

Few shot object detection for headdresses and seats in Thangka Yidam based on ResNet and deformable convolution

Published:2022-02-23 Issue:1 Volume:34 Page:732-748
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Wenjin Hu¹²,Panpan Xue¹²,Guoyuan He¹³,Huiyuan Tang¹³,Huafei Song¹³,Chaoyang Yue¹³

Affiliation:

1. Key Laboratory of China’s Ethnic Languages and Information Technology of Ministry of Education, Northwest Minzu University, Lanzhou, People’s Republic of China

2. School of Mathematics and Computer Science, Northwest Minzu Univsersity, Lanzhou, People’s Republic of China

3. National Languages Information Technology, Boulder, Northwest Minzu University, Lanzhou, People’s Republic of China

Funder

the National Natural Science Foundation of China under grant

the Fundamental Research Funds for the Central Universities under Grant

the program for innovative research team of SEAC

the Northwest Minzu University Graduate Research Innovation Project

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2041554

Reference31 articles.

1. Soft-NMS — Improving Object Detection with One Line of Code

2. Memory Matching Networks for One-Shot Image Recognition

3. LSTD: A Low-Shot Transfer Detector for Object Detection

4. A novel general kernel-based non-negative matrix factorisation approach for face recognition

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