@article{tran_sakla_krim_2022, title={SAR Self-Enhanced by Electro-optical Network (SARSEEN)}, volume={12122}, ISBN={["978-1-5106-5120-3"]}, ISSN={["1996-756X"]}, DOI={10.1117/12.2618829}, abstractNote={We investigate the relationship between paired SAR and optical images. SAR sensors have the capabilities of penetrating clouds and capturing data at night, whereas optical sensors cannot. We are interested in the case where we have access to both modalities during training, but only the SAR during test time. To that end, we developed a framework that inputs a SAR image and predicts a Canny edge map of the optical image, which retains structural information, while removing superfluous details. Our experiments show that by additionally using this predicted edge map for downstream tasks, we can outperform the same model that only uses the SAR image.}, journal={SIGNAL PROCESSING, SENSOR/INFORMATION FUSION, AND TARGET RECOGNITION XXXI}, author={Tran, Kenneth and Sakla, Wesam and Krim, Hamid}, year={2022} }
 @article{tran_sakla_krim_2021, title={GENERATIVE INFORMATION FUSION}, DOI={10.1109/ICASSP39728.2021.9414284}, abstractNote={In this work, we demonstrate the ability to exploit sensing modalities for mitigating an unrepresented modality or for potentially re-targeting resources. This is tantamount to developing proxy sensing capabilities for multi-modal learning. In classical fusion, multiple sensors are required to capture different information about the same target. Maintaining and collecting samples from multiple sensors can be financially demanding. Additionally, the effort necessary to ensure a logical mapping between the modalities may be prohibitively limiting. We examine the scenario where we have access to all modalities during training, but only a single modality at testing. In our approach, we initialize the parameters of our single modality inference network with weights learned from the fusion of multiple modalities through both classification and GANs losses. Our experiments show that emulating a multi-modal system by perturbing a single modality with noise can help us achieve competitive results compared to using multiple modalities.}, journal={2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021)}, author={Tran, Kenneth and Sakla, Wesam and Krim, Hamid}, year={2021}, pages={3990–3994} }