An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...
Abstract: To address low-quality pseudo-labels and class imbalance in semi-supervised remote sensing scene classification, this letter proposes a novel dynamic adaptive reweighting and pseudo-labeling ...
Abstract: The limited availability of annotated training data significantly constrains the classification accuracy of hyperspectral image (HSI) and LiDAR fusion approaches. Although contrastive ...
What is supervised learning and how does it work? In this video/post, we break down supervised learning with a simple, real-world example to help you understand this key concept in machine learning.
Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. As machine learning continues to reshape the financial ...
Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...
ABSTRACT: The stochastic configuration network (SCN) is an incremental neural network with fast convergence, efficient learning and strong generalization ability, and is widely used in fields such as ...
A new technical paper titled “Semi-Supervised Learning with Wafer-Specific Augmentations for Wafer Defect Classification” was published by researchers at Korea University. “Semi-supervised learning ...
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