ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2505.01313
50
0

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

2 May 2025
Shang Wang
Huanrong Tang
Jianquan Ouyang
ArXivPDFHTML
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.

View on arXiv
@article{wang2025_2505.01313,
  title={ A Neural Architecture Search Method using Auxiliary Evaluation Metric based on ResNet Architecture },
  author={ Shang Wang and Huanrong Tang and Jianquan Ouyang },
  journal={arXiv preprint arXiv:2505.01313},
  year={ 2025 }
}
Comments on this paper