Measuring Modality Utilization in Multi-Modal Neural Networks-Reference-Cited by-同舟云学术

Measuring Modality Utilization in Multi-Modal Neural Networks

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Conference on Artificial Intelligence (CAI)
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Author:

Singh Saurav¹,Markopoulos Panos P.²,Saber Eli¹,Lew Jesse D.³,Heard Jamison¹

Affiliation:

1. Rochester Institute of Technology,Dept. Elect. & Microelectronic Eng.,Rochester,NY,USA

2. The University of Texas at San Antonio,Dept. Elect. & Comput. Eng. and Dept. Comput. Science,San Antonio,TX,USA

3. New York University,Dept. Computer Science,New York,NY,USA

Funder

Air Force Office of Scientific Research

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10194967/10194965/10195122.pdf?arnumber=10195122

Reference17 articles.

1. Deep learning in multimodal remote sensing data fusion: A comprehensive review

2. Multimodal Machine Learning: A Survey and Taxonomy

3. Exploring Cross-Modality Utilization in Recommender Systems

4. Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks;wu;Proc of the 39th Int Conf on Mach Learn (ICML),2022

5. Robust Face Recognition Using the Deep C2D-CNN Model Based on Decision-Level Fusion

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