# Application of Convolutional Neural Network for Image Classification on Pascal VOC Challenge 2012 dataset

Source: [Application of Convolutional Neural Network for Image Classification on Pascal VOC Challenge 2012 dataset](<https://www.sota2.com/research/paper/68fa629b1e209131ce9fa1ec>)

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

Data updated: 2025-10-25T20:22:26.903Z

Authors: Suyash Shetty

Published: 2016-07-13T15:18:25.000Z

## Abstract

In this project we work on creating a model to classify images for the Pascal VOC Challenge 2012. We use convolutional neural networks trained on a single GPU instance provided by Amazon via their cloud service Amazon Web Services (AWS) to classify images in the Pascal VOC 2012 data set. We train multiple convolutional neural network models and finally settle on the best model which produced a validation accuracy of 85.6% and a testing accuracy of 85.24%.

## 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/1607.03785>)

[PDF](<https://arxiv.org/pdf/1607.03785.pdf>)