Test:No pubyear UsingConvolutionalNeuralN

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Subject Headings: Convolution Neural Network; Yelp Image Classification Kaggle Challenge; Vggnet; Multiple Instance Learning (Mil) Model; Transfer Learning System; Imagenet Dataset

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Abstract

For the Yelp Image Classification Kaggle Challenge, we use a modified VGGNet to make predictions on 9 specific attributes of restaurants based on images by performing transfer learning. We explore two approaches to making these predictions: a naive model that assigns the attributes of the restaurant to each picture, and a more sophisticated method called multiple instance learning. With our naive model, we achieved a mean F1 score of 0.533, while our MIL model achieved a mean F1 score of 0.618. We then explore and evaluate other past methods attempted for this challenge and note various methods of improvement on our current models.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
No pubyear UsingConvolutionalNeuralNDiveesh Singh
Pedro Garzon
Using Convolutional Neural Networks and Transfer Learning to Perform Yelp Restaurant Photo Classification