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ALoRA: Allocating Low-Rank Adaptation for Fine-tuning Large Language Models
Parameter-efficient fine-tuning (PEFT) is widely studied for its effectiveness and efficiency in the era of large language models.
Image super-resolution reconstruction based on attention mechanism and feature fusion
Aiming at the problems that the convolutional neural networks neglect to capture the inherent attributes of natural images and extract features only in a single scale in the field of image super-resolution reconstruction, a network structure based on attention mechanism and multi-scale feature fusion is proposed.
Multi-Level Feature Fusion Mechanism for Single Image Super-Resolution
However, most SISR methods based on CNN do not make full use of hierarchical feature and the learning ability of network.
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