# Training Convolutional Networks with Web Images

Source: [Training Convolutional Networks with Web Images](<https://www.sota2.com/research/paper/68fa64601e209131cea041ee>)

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

Data updated: 2025-10-25T21:02:11.964Z

Authors: Nizar Massouh

Published: 2018-05-22T06:11:00.000Z

## Abstract

In this thesis we investigate the effect of using web images to build a large scale database to be used along a deep learning method for a classification task. We replicate the ImageNet large scale database (ILSVRC-2012) from images collected from the web using 4 different download strategies varying: the search engine, the query and the image resolution. As a deep learning method, we will choose the Convolutional Neural Network that was very successful with recognition tasks; the AlexNet.

## 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/1805.08416>)

[PDF](<https://arxiv.org/pdf/1805.08416.pdf>)