3 papers
cs.CV2025
Visual Explanation via Similar Feature Activation for Metric Learning
Yi Liao, Ugochukwu Ejike Akpudo, Jue Zhang +4
Visual explanation maps enhance the trustworthiness of decisions made by deep learning models and offer valuable guidance for developing new algorithms in image recognition tasks.…
cs.CV2025
TraNCE: Transformative Non-linear Concept Explainer for CNNs
Ugochukwu Ejike Akpudo, Yongsheng Gao, Jun Zhou +1
Convolutional neural networks (CNNs) have succeeded remarkably in various computer vision tasks. However, they are not intrinsically explainable. While the feature-level understand…
cs.CV2024
SATA: Spatial Autocorrelation Token Analysis for Enhancing the Robustness of Vision Transformers
Nick Nikzad, Yi Liao, Yongsheng Gao +1
Over the past few years, vision transformers (ViTs) have consistently demonstrated remarkable performance across various visual recognition tasks. However, attempts to enhance thei…