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

Source: [Analysis of convolutional neural network image classifiers in a hierarchical max-pooling model with additional local pooling](<https://www.sota2.com/research/paper/68fa6a1e1e209131cea2608d>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T23:16:37.291Z

Authors: Benjamin Walter

Published: 2021-05-31T16:08:00.000Z

## Abstract

Image classification is considered, and a hierarchical max-pooling model with additional local pooling is introduced. Here the additional local pooling enables the hierachical model to combine parts of the image which have a variable relative distance towards each other. Various convolutional neural network image classifiers are introduced and compared in view of their rate of convergence. The finite sample size performance of the estimates is analyzed by applying them to simulated and real data.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2106.05233>)

[PDF](<https://arxiv.org/pdf/2106.05233.pdf>)