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

Dynamic Spatial-Temporal Graph Convolutional Neural Networks Approach for Active Mode Traffic Prediction

Abstract: Accurate short-term predictions of active mode traffic are crucial for effective urban traffic control and management, helping to reduce delays, stops, and improve travel time reliability, ...
IEEE

Multi-Branch Multi-Scale Channel Fusion Graph Convolutional Networks With Transfer Cost for Robotic Tactile Recognition Tasks

Abstract: Inadequate consideration of tactile sensor features in existing algorithms can lead to insufficient prediction accuracy for robotic tactile recognition tasks. In this paper, we propose a ...