Addressing the Challenge of Ambiguous Data in Deep Learning
Lars Schmarje
Abstract:In machine learning, the availability of high-quality labeled data is essential for training accurate models. However, humans often disagree among themselves or over time when labeling or annotating image classification data. As a result, they create ambiguous data that poses a significant challenge to deep learning.
This research focuses on addressing this issue by proposing an overview that defines the problem, provides the necessary data for research, establishes evaluation metrics and p… Show more
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