Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling-Reference-Cited by-同舟云学术

Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling

Published:2023-05 Issue: Volume:224 Page:109-126
ISSN:0378-3758
Container-title:Journal of Statistical Planning and Inference
language:en
Short-container-title:Journal of Statistical Planning and Inference

Author:

Walter Benjamin^ORCID

Funder

Deutsche Forschungsgemeinschaft

Publisher

Elsevier BV

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability

Reference44 articles.

1. Convexity, classification, and risk bounds;Bartlett;J. Amer. Statist. Assoc.,2006

2. On deep learning as a remedy for the curse of dimensionality in nonparametric regression;Bauer;Ann. Statist.,2019

3. Convergence rates of deep ReLU networks for multiclass classification;Bos,2021

4. Boureau, Y.-L., Ponce, J., Lecun, Y., 2010. A Theoretical Analysis of Feature Pooling in Visual Recognition. In: Proceedings of the 27th International Conference on Machinelearning (ICML-10). pp. 111–118.

5. Keras;Chollet,2015

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. CNN vs. LSTM: A Comparative Study of Hourly Precipitation Intensity Prediction as a Key Factor in Flood Forecasting Frameworks;Atmosphere;2024-09-06

2. Optimization of Chinese film and television communication technology in Portuguese-speaking areas under the application of digital Internet of Things;Heliyon;2024-09

3. Fault-MTL: A Multi-task Deep Learning Approach for Simultaneous Fault Classification and Localization in Power Systems;Journal of Control, Automation and Electrical Systems;2024-08-11

4. Deep learning on medical image analysis;CAAI Transactions on Intelligence Technology;2024-06-24

5. A fine digital soil mapping by integrating remote sensing-based process model and deep learning method in Northeast China;Soil and Tillage Research;2024-05