A Neural Architecture Search Method using Auxiliary Evaluation Metric based on ResNet Architecture

• URL: http://arxiv.org/abs/2505.01313v1
• Date: Fri, 02 May 2025 14:39:44 GMT
• Title: A Neural Architecture Search Method using Auxiliary Evaluation Metric based on ResNet Architecture
• Authors: Shang Wang, Huanrong Tang, Jianquan Ouyang,
• Abstract summary: This paper proposes a neural architecture search space using ResNet as a framework, with search objectives including parameters for convolution, pooling, fully connected layers, and connectivity of the residual network.<n>The experimental results demonstrate that the search space of this paper together with the optimisation approach can find competitive network architectures on the MNIST, Fashion-MNIST and CIFAR100 datasets.
• Score: 2.498836880652668
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper proposes a neural architecture search space using ResNet as a framework, with search objectives including parameters for convolution, pooling, fully connected layers, and connectivity of the residual network. In addition to recognition accuracy, this paper uses the loss value on the validation set as a secondary objective for optimization. The experimental results demonstrate that the search space of this paper together with the optimisation approach can find competitive network architectures on the MNIST, Fashion-MNIST and CIFAR100 datasets.

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