# Advancements in Image Classification using Convolutional Neural Network

Source: [Advancements in Image Classification using Convolutional Neural Network](<https://www.sota2.com/research/paper/68fa65c31e209131cea0c462>)

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

Data updated: 2025-10-25T21:34:37.515Z

Authors: Farhana Sultana, A. Sufian, Paramartha Dutta

Published: 2019-05-08T18:34:19.000Z

## Abstract

Convolutional Neural Network (CNN) is the state-of-the-art for image classification task. Here we have briefly discussed different components of CNN. In this paper, We have explained different CNN architectures for image classification. Through this paper, we have shown advancements in CNN from LeNet-5 to latest SENet model. We have discussed the model description and training details of each model. We have also drawn a comparison among those models.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1905.03288>)

[PDF](<https://arxiv.org/pdf/1905.03288.pdf>)