arXiv AI By Amin Doroodchi, Danial Soleimany

Using the YOLOv12 Model for Verifying the Correct Color Sequence of Wires in Network Cables (Patch Cords) on the Production Line

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arXiv:2606. 10699v1 Announce Type: cross Abstract: In the production process of network cables, ensuring the correct color sequence of wire pairs inside the standard connector plays a critical role in the final performance of the cable, as any misplacement or color-ordering error can lead to defective products and impose significant costs.

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

arXiv:2604. 26633v2 Announce Type: replace-cross Abstract: Industrial surface defect inspection suffers from a fundamental data bottleneck: defects are rare, annotations require expert knowledge, and collecting balanced training sets is slow and costly.

By Paul Julius K\"uhn, Mika Pommeranz, Arjan Kuijper, Saptarshi Neil Sinha
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A Comparative Evaluation of Deep Learning Object Detection Models on a Real-World Multi-Plant Dataset from Africa

arXiv:2608. 11053v1 Announce Type: cross Abstract: The application of computer vision in agriculture has shown significant potential for improving crop monitoring and precision farming.

By Ismail Ismail Tijjani, Sunusi Muhammad Ibrahim, Amina Ibrahim Khaleel, Lanre Olusegun Akinola, Fatima Isa Jibrin, Muhammad Bashir Aliyu, Abdullahi Abdussalam Dalhat, Abdullahi Suiudeen