RSITR-FFT: Efficient Fine-Grained Fine-Tuning Framework With Consistency Regularization for Remote Sensing Image-Text Retrieval

Di Xiu; Luyan Ji; Xiurui Geng; Yirong Wu

doi:10.1109/lgrs.2024.3478176

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RSITR-FFT: Efficient Fine-Grained Fine-Tuning Framework With Consistency Regularization for Remote Sensing Image-Text Retrieval

Di Xiu Luyan Ji Xiurui Geng Yirong Wu

Year: 2024 Journal: IEEE Geoscience and Remote Sensing Letters Vol: 21 Pages: 1-5 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/lgrs.2024.3478176

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Keywords:

Computer science Regularization (linguistics) Fast Fourier transform Consistency (knowledge bases) Image retrieval Remote sensing Computer graphics (images) Image (mathematics) Computer vision Information retrieval Artificial intelligence Algorithm Geology

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Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

RSITR-FFT: Efficient Fine-Grained Fine-Tuning Framework With Consistency Regularization for Remote Sensing Image-Text Retrieval

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