Exploring the Horizons of Meta-Learning in Neural Networks: A Survey of the State-of-the-Art
In the vast landscape of machine learning, meta-learning stands out as a challenging and
dynamic area of exploration. While traditional machine learning models rely on standard …
dynamic area of exploration. While traditional machine learning models rely on standard …
Quantum few-shot image classification
Z Huang, J Shi, X Li - IEEE Transactions on Cybernetics, 2024 - ieeexplore.ieee.org
Few-shot learning algorithms frequently exhibit suboptimal performance due to the limited
availability of labeled data. This article presents a novel quantum few-shot image …
availability of labeled data. This article presents a novel quantum few-shot image …
[HTML][HTML] Multi-task convex combination interpolation for meta-learning with fewer tasks
Y Tang, L Zhang, W Zhang, Z Jiang - Knowledge-Based Systems, 2024 - Elsevier
Meta-learning methods try to enhance the generalization of the meta-learning model by
various tasks. Diverse tasks can provide sufficient knowledge to assist the model in …
various tasks. Diverse tasks can provide sufficient knowledge to assist the model in …
Fortifying Fully Convolutional Generative Adversarial Networks for Image Super-Resolution Using Divergence Measures
Super-Resolution (SR) is a time-hallowed image processing problem that aims to improve
the quality of a Low-Resolution (LR) sample up to the standard of its High-Resolution (HR) …
the quality of a Low-Resolution (LR) sample up to the standard of its High-Resolution (HR) …