Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
To explain how a convolutional neural network (CNN) processes an image, it is common to generate classification activation maps (CAMs) to reveal image areas that are relevant to output. Nevertheless, ...
Finally, it generates an attention map and multiplies it element-wise with the input feature map to refine the features. “Visualizing convolutional neural networks through Grad-CAM more clearly shows ...
Purpose: Accurate differentiation between glioma recurrence and radiation necrosis is critical for the management of patients suspected of glioma recurrence following radiation therapy. This study ...
A comprehensive PyTorch-based system for predicting cryptocurrency prices using a state-of-the-art Spatial-Temporal Graph Neural Network (ST-GNN) model. This advanced implementation integrates ...
ABSTRACT: The COVID-19 pandemic has profoundly impacted global health, with far-reaching consequences beyond respiratory complications. Increasing evidence highlights the link between COVID-19 and ...
Last Monday marked the beginning of Love Data Week, hosted by the Connolly Alexander Institute for Data Science in conjunction with the Tulane University Libraries. Love Data Week featured lectures, ...
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