From Coarse to Fine: Knowledge Distillation for Remote Sensing Scene Classification-Reference-Cited by-同舟云学术

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From Coarse to Fine: Knowledge Distillation for Remote Sensing Scene Classification

Published:2023-07-16 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Ji Jinsheng¹,Xi Xiaoming²,Lu Xiankai³,Guo Yiyou⁴,Xie Huan⁴

Affiliation:

1. Nanyang Technological University,School of Electrical and Electronic Engineering,Singaproe,639798

2. Shandong Jianzhu University,School of Computer Science and Technology,Jinan,China,250101

3. Shandong University,School of Software,Jinan,China,250101

4. Tongji University,College of Surveying and Geo-Informatics,Shanghai,China,200092

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10281394/10281399/10282366.pdf?arnumber=10282366

Reference12 articles.

1. Remote Sensing Scene Image Classification Based on Self-Compensating Convolution Neural Network

2. Classification of High-Spatial-Resolution Remote Sensing Scenes Method Using Transfer Learning and Deep Convolutional Neural Network

3. Visualizing data using t-sne;van der maaten;Journal of Machine Learning Research,2008

4. AID: A Benchmark Data Set for Performance Evaluation of Aerial Scene Classification

5. Self-Attention-Based Deep Feature Fusion for Remote Sensing Scene Classification

Cited by 1 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. DC-KD: double-constraint knowledge distillation for optical satellite imagery object detection based on YOLOX model;Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023);2024-05-22

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