Isaac is a fourth year undergraduate student in electrical engineering, specializing in control systems. Previously he was a member of UW’s Formula SAE team where he brought up both hardware and firmware. From there, he interned at Apple on their iPhone hardware org for several months, working primarily on power integrity and test automation. Currently, his interests lie at the intersection of embedded computer systems and control theory. At CTRL, he will be developing the hardware and software stack for drones. Outside of school, he enjoys cooking, reading, weightlifting, and hiking.
Publications
MISFIT-V: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual
Detecting humans from airborne visual and thermal imagery is a fundamental challenge for Wilderness Search-and-Rescue (WiSAR) teams, who must perform this function accurately in the face of immense pressure. The ability to fuse these two sensor modalities can potentially reduce the cognitive load on human operators and/or improve the effectiveness of computer vision object detection models. However, the fusion task is particularly challenging in the context of WiSAR due to hardware limitations and extreme environmental factors. This work presents Misaligned Image Synthesis and Fusion using Information from Thermal and Visual (MISFIT-V), a novel two-pronged unsupervised deep learning approach that utilizes a Generative Adversarial Network (GAN) and a cross-attention mechanism to capture the most relevant features from each modality. Experimental results show MISFIT-V offers enhanced robustness against misalignment and poor lighting/thermal environmental conditions compared to existing visual-thermal image fusion methods.
@inproceedings{ChauhanRemyEtAl2023,author={Chauhan, A. and Remy, I. and Broyles, D. and Leung, K.},title={{MISFIT-V}: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual},year={2023},arxiv={2309.13216},img={ChauhanRemyEtAl2023.png},note={(submitted)},keywords={preprint},owner={karenl7}}
Semantically-Driven Object Search Using Partially Observed 3D Scene Graphs
@inproceedings{RemyGuptaEtAl2024,author={Remy, I. and Gupta, A. and Leung, K.},title={Semantically-Driven Object Search Using Partially Observed {3D} Scene Graphs},year={2024},img={RemyGuptaEtAl2024.png},note={(preprint)},keywords={preprint},owner={karenl7}}
