Posts by Max Kiehn

Semantic Fencing of Video Streams Using Embedding Splits from Vision Foundation Models

In this blog, we present a novel approach for semantically splitting vision datasets into training, validation, and test sets. Instead of relying on ad hoc metadata rules or random shuffles, we use embeddings to reason directly about similarity in latent space and construct splits that better reflect true generalization.

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