Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition

By Seungwhan Moon, Suyoun Kim, Haohan Wang. 2014

33 citations recorded by the source corpus.

Subfields: Multimodal Learning, Representation & Self-Supervised Learning

How researchers see this paper

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

In Multimodal Learning

1. Stefan Wermter
2. German Ignacio Parisi
3. Christopher Kanan
4. Kushal Kafle
5. Manoj Acharya
6. Robik Shrestha

In Representation & Self-Supervised Learning

1. Christopher Kanan
2. Stefan Wermter
3. Rajen Subba
4. Anuj Kumar
5. Pararth Shah
6. Jose L. Part
7. Seungwhan Moon
8. German Ignacio Parisi

Citations in the corpus

• Continual Lifelong Learning with Neural Networks: A Review (2018, background): “, in terms of learned associations), scaffolding perception, cognition, and behaviour (see Murray et al. (2016) and Stein et al. (2014) for reviews).”
• OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs (2019, background): “( TL:FT) transfers knowledge from a pre-trained source model via fine-tuning (hence requiring significantly less training resources), and effectively avoids “cold start” training (Moon et al., 2015).”