Kayacan, Yavuz EmreErer, Isin2025-03-092025-03-092024979-835039105-3https://doi.org/10.1109/TELFOR63250.2024.10819108https://hdl.handle.net/20.500.12662/490932nd Telecommunications Forum, TELFOR 2024 -- 26 November 2024 through 27 November 2024 -- Belgrade -- 205822Traditional clutter removal methods struggle with complex clutter and multiple targets in Ground-Penetrating Radar images. This study proposes using B-spline activation functions in the deep-learning models to improve clutter removal in GPR. Experimental results demonstrate that B-spline-enhanced models outperform their ReLU-based counterparts, with improvements of up to 2.20% in PSNR, 0.035% in MS-SSIM, and 15.83% in SCR, showcasing their potential for real-world GPR applications. © 2024 IEEE.eninfo:eu-repo/semantics/closedAccessB-splinesClutter removaldeep learningground-penetrating radarEnhancing Deep Learning Networks Performance By Using B-Spline Activation Functions for Clutter Removal in GPRConference Object10.1109/TELFOR63250.2024.108191082-s2.0-85216891208N/A