Intelligent fault diagnosis aims to build robust mechanical condition recognition models with
limited dataset. At this stage, fault diagnosis faces two practical challenges:(1) the variability …

Encounters between humans and wildlife often lead to injuries, especially in remote
wilderness regions, and highways. Therefore, animal detection is a vital safety and wildlife …

Reinforcement learning continuously optimizes decision-making based on real-time
feedback reward signals through continuous interaction with the environment …

The detection of rail surface defects is very important in railway transportation. However, the
edge defects on both sides of the rail and the multi-scale variation between different types of …

Remote sensing object detection is an essential task for surveying the earth. It is challenging
for the target detection algorithm in natural scenes to obtain satisfactory detection results in …

Albeit recent cross-modal crowd counting methods have achieved promising performance,
most of them only focus on how to combine the RGB modality and thermal modality, and …

Purpose: Visual perception enables robots to perceive the environment. Visual data is
processed using computer vision algorithms that are usually time-expensive and require …

In printed circuit board (PCB) defect detection, it is difficult to collect defect samples, and the
detection effect is poor due to the lack of data. On the basis of the few-shot learning method …

Maintenance tasks in distribution networks are often accompanied by hazards associated
with high altitudes and high voltages. By utilising robots instead of human operators to …

The damage of wind turbine blades is one of the main problems restricting wind power
development. Object detection can identify the damaged regions and diagnose the damage …