Person re-identification (Re-ID) has undergone a rapid development with the blooming of
deep neural network. Most methods are very easily affected by target misalignment and …

Abstract Person re-identification (ReId), a crucial task in surveillance, involves matching
individuals across different camera views. The advent of Deep Learning, especially …

To improve the efficiency of deep reinforcement learning (DRL)-based methods for robotic
trajectory planning in the unstructured working environment with obstacles. Different from …

Face recognition has achieved unprecedented results, surpassing human capabilities in
certain scenarios. However, these automatic solutions are not ready for production because …

Electroencephalography (EEG) is a commonly used clinical approach for the diagnosis of
epilepsy which is a life-threatening neurological disorder. Many algorithms have been …

Existing vehicle re-identification (Re-ID) methods usually combine global features and local
features to meet the challenge of inter-class similarity and intra-class variance, but almost all …

Semi-supervised learning is important and has become more widespread because
obtaining labeled data is expensive and labor-intensive. In this paper, we focus on the …

Learning the similarity between remote sensing (RS) images forms the foundation for
content-based RS image retrieval (CBIR). Recently, deep metric learning approaches that …

Fault detection plays an essential role in the power generation of wind turbines (WTs).
However, most of the present fault detection methods are designed to detect a certain type of …

The critical technology of the broccoli selective harvesting robot centres around the maturity
identification and determination of broccoli heads suitable for harvesting. To address this …