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cs.CV2024
Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network
Bin Cheng, Jiaxuan Lu
With the advent of the era of foundation models, pre-training and fine-tuning have become common paradigms. Recently, parameter-efficient fine-tuning has garnered widespread attent…
cs.CV2023
Impact of Label Types on Training SWIN Models with Overhead Imagery
Ryan Ford, Kenneth Hutchison, Nicholas Felts +3
Understanding the impact of data set design on model training and performance can help alleviate the costs associated with generating remote sensing and overhead labeled data. This…