5 papers
JA-SIREN: Deterministic Initialization for Sinusoidal Networks via Spectral Matching
Mohammed Alsakabi, Kejia Hu, John M. Dolan +1
Existing implicit neural representation (INR) approaches suffer from stochastic initialization that does not guarantee consistent or high-quality performance across runs, with vari…
FM-SIREN & FM-FINER: Implicit Neural Representation Using Nyquist-based Orthogonality
Mohammed Alsakabi, Wael Mobeirek, John M. Dolan +1
Existing periodic activation-based implicit neural representation (INR) networks, such as SIREN and FINER, suffer from hidden feature redundancy, where neurons within a layer captu…
Reproducing and Extending RaDelft 4D Radar with Camera-Assisted Labels
Kejia Hu, Mohammed Alsakabi, John M. Dolan +1
Recent advances in 4D radar highlight its potential for robust environment perception under adverse conditions, yet progress in radar semantic segmentation remains constrained by t…
The Impact of 2D Segmentation Backbones on Point Cloud Predictions Using 4D Radar
William Muckelroy, Mohammed Alsakabi, John Dolan +1
LiDAR's dense, sharp point cloud (PC) representations of the surrounding environment enable accurate perception and significantly improve road safety by offering greater scene awar…
Toward a Low-Cost Perception System in Autonomous Vehicles: A Spectrum Learning Approach
Mohammed Alsakabi, Aidan Erickson, John M. Dolan +1
We present a cost-effective new approach for generating denser depth maps for Autonomous Driving (AD) and Autonomous Vehicles (AVs) by integrating the images obtained from deep neu…