eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

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 ...
IEEE

Attention-Enhanced Graph Convolution Network for Malware Family Feature Extraction and Embedding

Abstract: Understanding malware from its dynamic API call sequence is non-trivial, since the length of a call sequence might be long and the important calls might be neglected by human beings. In ...
IEEE

MBGCN: Multi-view Block-wise Graph Convolutional Networks on Large-scale Graphs

Abstract: Existing methods based on graph convolutional network often struggle with large-scale graphs due to their high computing consumption and inefficiency. Although strategies such as edge ...
Frontiers

Crack detection in structural images using a hybrid Swin Transformer and enhanced features representation block

1 Department of IoT, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India 2 School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, ...