Multimodal Classification Fusion in Real-World Scenarios

By Ignazio Gallo, Alessandro Calefati, Shah Nawaz. 2017

42 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Multimodal Learning

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Douwe Kiela
2. Vedanuj Goswami
3. Amanpreet Singh
4. Davide Testuggine
5. Pratik Ringshia
6. Aravind Mohan
7. Hamed Firooz
8. Mohit Bansal

In Multimodal Learning

1. Davide Testuggine
2. Pratik Ringshia
3. Douwe Kiela
4. Aravind Mohan
5. Hamed Firooz
6. Vedanuj Goswami
7. Amanpreet Singh
8. Ronghang Hu

Citations in the corpus

• The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes (2020, methodology): “Other datasets using internet data include Food101 [80], where the goal is to predict the dish of recipes and images; various versions of Yelp reviews [52]; Walmart and Ferramenta product classification [90, 21]; social media name tagging (Twitter and Snapchat) [49]; social media target-oriented sen”