In this paper, a novel telescopic broad Bayesian learning (TBBL) is proposed for sequential
learning. Conventional broad learning suffers from the singularity problem induced by the …

Stroke patients are prone to fatigue during the EEG acquisition procedure, and experiments
have high requirements on cognition and physical limitations of subjects. Therefore, how to …

Zero-shot object detection aims to identify objects from unseen categories not present during
training. Existing methods rely on category labels to create pseudo-features for unseen …

Deep Feedforward Neural Networks (FNNs) with skip connections have revolutionized
various image recognition tasks. In this paper, we propose a novel architecture called …

Reinforcement learning (RL) is a powerful technique that allows agents to learn optimal
decision-making policies through interactions with an environment. However, traditional RL …

2 S. Meng et al. with the most relevant image regions. Specifically, our label-based attention,
guided by the latent label embedding, captures discriminative image details. To distinguish …