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Benjamin El-Zein

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#machine learning Preprint Sep 2026

Soft-Argmax for the Projective Plane via the Veronese Embedding

The Veronese soft-argmax is validated in a Hough transform-based network across all resolvable lines, confirming uniform and seam-free recovery and the squared chordal distance between lines in projective space is derived, enabling a geometrically precise training objective.

Benjamin El-Zein, Dominik Eckert, Paul Zech et al. · 0 citations

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