3 papers
cs.LG2025
Semantic-Aware Gaussian Process Calibration with Structured Layerwise Kernels for Deep Neural Networks
Kyung-hwan Lee, Kyung-tae Kim
Calibrating the confidence of neural network classifiers is essential for quantifying the reliability of their predictions during inference. However, conventional Gaussian Process…
cs.CV2024
Adaptive Residual Transformation for Enhanced Feature-Based OOD Detection in SAR Imagery
Kyung-hwan Lee, Kyung-tae Kim
Recent advances in deep learning architectures have enabled efficient and accurate classification of pre-trained targets in Synthetic Aperture Radar (SAR) images. Nevertheless, the…
cs.CV2024
IRASNet: Improved Feature-Level Clutter Reduction for Domain Generalized SAR-ATR
Oh-Tae Jang, Min-Jun Kim, Sung-Ho Kim +2
Recently, computer-aided design models and electromagnetic simulations have been used to augment synthetic aperture radar (SAR) data for deep learning. However, an automatic target…