arXiv Machine Learning July 8, 2026 By Keonvin Park, Yong Ann Voeurn, Hyeokjun Kweon, Doyun Lee

Enhanced Seam Segmentation for Automated Welding Robot in Construction Through Transfer Learning: Addressing Limitations of Bilateral Segmentation Network

Read the original on arXiv Machine Learning →

arXiv:2607. 06150v1 Announce Type: cross Abstract: Reliable seam segmentation is essential for autonomous robotic welding in construction, where harsh illumination, specular reflections, and thin weld geometries often degrade segmentation performance.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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A multi-task spatiotemporal deep neural network for predicting penetration depth and morphology in laser welding

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SynSur: An end-to-end generative pipeline for synthetic industrial surface defect generation and detection

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