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

Combining Reinforcement Learning and Heuristic Optimization: A Model Based on a Deep Q-Network and Graph Neural Networks for Graph Coloring

Abstract: We present a hybrid approach combining Reinforcement Learning (RL) with the TabuCol, which is a version of tabu search specifically designed for the Graph Coloring Problem (GCP), enhanced by ...
IEEE

Spatial-Spectral Contrastive Graph Neural Network for Few-Shot Hyperspectral Image Classification

Abstract: Graph Neural Networks (GNNs) have emerged as a promising solution for few-shot hyperspectral image (HSI) classification. However, existing GNN-based approaches face critical limitations in ...