mlsanityData to 7 Oct 2026

From Xception to NEXcepTion: New Design Decisions and Neural Architecture Search

arXiv 2212.08448 ↗First posted 16 Dec 2022cs.CV cs.AIcited by 0

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Abstract (arXiv)

In this paper, we present a modified Xception architecture, the NEXcepTion network. Our network has significantly better performance than the original Xception, achieving top-1 accuracy of 81.5% on the ImageNet validation dataset (an improvement of 2.5%) as well as a 28% higher throughput. Another variant of our model, NEXcepTion-TP, reaches 81.8% top-1 accuracy, similar to ConvNeXt (82.1%), while having a 27% higher throughput. Our model is the result of applying improved training procedures and new design decisions combined with an application of Neural Architecture Search (NAS) on a smaller dataset. These findings call for revisiting older architectures and reassessing their potential when combined with the latest enhancements.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 35 of its 47 references that are in the map. First posted on arXiv 16 Dec 2022.

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35 of 47 references.

References · 35

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23 more
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