Class Incremental Learning With Few-Shots Based on Linear Programming for Hyperspectral Image Classification

Author:

Bai JingORCID,Yuan Anran,Xiao ZhuORCID,Zhou HuajiORCID,Wang Dingchen,Jiang HongboORCID,Jiao LichengORCID

Funder

State Key Program of National Natural Science of China

National Natural Science Foundation of China

Open Fund of Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education

Natural Resources Scientific Research Project of Department of the Natural Resources of Hunan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Human-Computer Interaction,Information Systems,Control and Systems Engineering,Software

Cited by 28 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. Integrating Prototype Learning With Graph Convolution Network for Effective Active Hyperspectral Image Classification;IEEE Transactions on Geoscience and Remote Sensing;2024

2. The Image Data and Backbone in Weakly Supervised Fine-Grained Visual Categorization: A Revisit and Further Thinking;IEEE Transactions on Circuits and Systems for Video Technology;2024-01

3. Class Incremental Learning Method for Hyperspectral Images Based on Real Data Playback Mechanism and Classification Network Optimization;Lecture Notes in Electrical Engineering;2024

4. Few-Shot Object Detection Based on Generalized Features;2023 2nd International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP);2023-10-27

5. Autonomous perception and adaptive standardization for few-shot learning;Knowledge-Based Systems;2023-10

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