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arXiv Computer Vision By Hao Tian, Jie Hu, Guoqi Shan, Fan Wang, Wenzhuo Zhang, Youshan Zhang

Selective Spatio-Temporal Fruit Inspector (S$^2$FI): A Mamba-based Framework for Rotational Fruit Quality Assessment

Read the original on arXiv Computer Vision →

The paper introduces the Selective Spatio-Temporal Fruit Inspector (S$^2$FI), a low‑cost, high‑efficiency fruit sorting system that uses a 3D convolutional encoder and a Mamba‑based backbone to extract spatiotemporal features and adaptively weight informative frames during fruit rotation. The hardware design features a dual‑conveyor and curved rail system powered by household electricity, enabling fast deployment and lightweight embedded operation. Experiments on a newly built dataset of 6,460 samples demonstrate that S$^2$FI achieves the best balance of accuracy, speed, and practicality compared to baseline methods.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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