Application of Convolutional Neural Network for Image Classification on Pascal VOC Challenge 2012 dataset
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Abstract (arXiv)
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%.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Jul 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 1.
3 papers.
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- 2025Object-Centric Cropping for Visual Few-Shot Classification31 Jul 2025
- 2023Advanced Efficient Strategy for Detection of Dark Objects Based on Spiking Network with Multi-Box Detection10 Oct 2023
- 2021Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions24 Feb 2021