A Novel lightweight Convolutional Neural Network, ExquisiteNetV2
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Abstract (arXiv)
In the paper of ExquisiteNetV1, the ability of classification of ExquisiteNetV1 is worse than DenseNet. In this article, we propose a faster and better model ExquisiteNetV2. We conduct many experiments to evaluate its performance. We test ExquisiteNetV2, ExquisiteNetV1 and other 9 well-known models on 15 credible datasets under the same condition. According to the experimental results, ExquisiteNetV2 gets the highest classification accuracy over half of the datasets. Important of all, ExquisiteNetV2 has fewest amounts of parameters. Besides, in most instances, ExquisiteNetV2 has fastest computing speed.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 19 May 2021.
Builds on
14 of 29 references.
References · 14
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Citing papers per year: 2023: 1; 2024: 0; 2025: 1.
2 papers.