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

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arxiv 1607.03785 v1 pith:S34ITARO submitted 2016-07-13 cs.CV

Suyash Shetty This is my paper
classification cs.CV
keywords convolutionalneuralpascalaccuracyamazonchallengeclassifyimages
verification ladder T0 review T1 audit T2 compute T3 formal
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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%.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Object-Centric Cropping for Visual Few-Shot Classification

    cs.CV 2025-07 unverdicted novelty 4.0 of 10

    The supplied full text (arXiv:2508.00225) is a different paper from the claimed metadata (arXiv:2508.00218), so no claim about few-shot classification is backed by the manuscript.

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