5 papers
Deep learning-based neurodevelopmental assessment in preterm infants
Lexin Ren, Jiamiao Lu, Weichuan Zhang +6
Preterm infants (born between 28 and 37 weeks of gestation) face elevated risks of neurodevelopmental delays, making early identification crucial for timely intervention. While dee…
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.…
Dynamic Accumulated Attention Map for Interpreting Evolution of Decision-Making in Vision Transformer
Yi Liao, Yongsheng Gao, Weichuan Zhang
Various Vision Transformer (ViT) models have been widely used for image recognition tasks. However, existing visual explanation methods can not display the attention flow hidden in…
Neuron Abandoning Attention Flow: Visual Explanation of Dynamics inside CNN Models
Yi Liao, Yongsheng Gao, Weichuan Zhang
In this paper, we present a Neuron Abandoning Attention Flow (NAFlow) method to address the open problem of visually explaining the attention evolution dynamics inside CNNs when ma…
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…