Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images-Reference-Cited by-同舟云学术

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Experience feedback using Representation Learning for Few-Shot Object Detection on Aerial Images

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)
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Author:

Jeune Pierre Le,Lebbah Mustapha,Mokraoui Anissa,Azzag Hanene

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9679834/9679948/09680249.pdf?arnumber=9680249

Reference20 articles.

1. RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

2. Few-Shot Object Detection via Feature Reweighting

3. Few-Shot Object Detection With Attention-RPN and Multi-Relation Detector

4. Few-Shot Object Detection With Self-Adaptive Attention Network for Remote Sensing Images

5. Few-Shot Object Detection via Knowledge Transfer

Cited by 4 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. Few-Shot Object Detection in Remote-Sensing Images via Label-Consistent Classifier and Gradual Regression;IEEE Transactions on Geoscience and Remote Sensing;2024

2. Cross-Scale Query-Support Alignment Approach for Small Object Detection in the Few-Shot Regime;2023 IEEE International Conference on Image Processing (ICIP);2023-10-08

3. Few-Shot Object Detection in Aerial Imagery Guided by Text-Modal Knowledge;IEEE Transactions on Geoscience and Remote Sensing;2023

4. Improving Few-Shot Object Detection through a Performance Analysis on Aerial and Natural Images;2022 30th European Signal Processing Conference (EUSIPCO);2022-08-29

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