2016 UsingConvolutionalNeuralNetwork

• (Singh & Garzon, 2016) ⇒ Diveesh Singh, and Pedro Garzon. (2016). “Using Convolutional Neural Networks and Transfer Learning to Perform Yelp Restaurant Photo Classification.”

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

Cited By

• Google Scholar: ~ 0 Citation.
• (Melli et al., 2020) ⇒ Gabor Melli, Abdelrhman Eldallal, Bassim Lazem, and Olga Moreira. (2020). “GM-RKB WikiText Error Correction Task and Baselines.” In: Proceedings of LREC 2020.

Quotes

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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2016 UsingConvolutionalNeuralNetwork	Gabor Melli Diveesh Singh Pedro Garzon Abdelrhman Eldallal Bassim Lazem Olga Moreira			Using Convolutional Neural Networks and Transfer Learning to Perform Yelp Restaurant Photo Classification