5 papers
Latent Code-Based Fusion: A Volterra Neural Network Approach
Sally Ghanem, Siddharth Roheda, Hamid Krim
We propose a deep structure encoder using the recently introduced Volterra Neural Networks (VNNs) to seek a latent representation of multi-modal data whose features are jointly cap…
Robust Multi-Modal Sensor Fusion: An Adversarial Approach
Siddharth Roheda, Hamid Krim, Benjamin S. Riggan
In recent years, multi-modal fusion has attracted a lot of research interest, both in academia, and in industry. Multimodal fusion entails the combination of information from a set…
Event Driven Fusion
Siddharth Roheda, Hamid Krim, Zhi-Quan Luo +1
This paper presents a technique which exploits the occurrence of certain events as observed by different sensors, to detect and classify objects. This technique explores the extent…
Decision Level Fusion: An Event Driven Approach
Siddharth Roheda, Hamid Krim, Zhi-Quan Luo +1
This paper presents a technique that combines the occurrence of certain events, as observed by different sensors, in order to detect and classify objects. This technique explores t…
Cross-Modality Distillation: A case for Conditional Generative Adversarial Networks
Siddharth Roheda, Benjamin S. Riggan, Hamid Krim +1
In this paper, we propose to use a Conditional Generative Adversarial Network (CGAN) for distilling (i.e. transferring) knowledge from sensor data and enhancing low-resolution targ…