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Automatic Prompt Generation and Grounding Object Detection for Zero-Shot Image Anomaly Detection
Tsun-Hin Cheung, Ka-Chun Fung, Songjiang Lai +3
Identifying defects and anomalies in industrial products is a critical quality control task. Traditional manual inspection methods are slow, subjective, and error-prone. In this wo…
Residual Attention Single-Head Vision Transformer Network for Rolling Bearing Fault Diagnosis in Noisy Environments
Songjiang Lai, Tsun-Hin Cheung, Jiayi Zhao +3
Rolling bearings play a crucial role in industrial machinery, directly influencing equipment performance, durability, and safety. However, harsh operating conditions, such as high…
An End-to-End Two-Stream Network Based on RGB Flow and Representation Flow for Human Action Recognition
Song-Jiang Lai, Tsun-Hin Cheung, Ka-Chun Fung +2
With the rapid advancements in deep learning, computer vision tasks have seen significant improvements, making two-stream neural networks a popular focus for video based action rec…
CBAM-SwinT-BL: Small Rail Surface Defect Detection Method Based on Swin Transformer with Block Level CBAM Enhancement
Jiayi Zhao, Alison Wun-lam Yeung, Ali Muhammad +2
Under high-intensity rail operations, rail tracks endure considerable stresses resulting in various defects such as corrugation and spellings. Failure to effectively detect defects…