Tag Archive
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A Peek into Automatic Data Augmentation by Policy Searching
When training a model based on machine-learning (ML) or deep-learning (DL), data augmentation (DA) is a crucial technique to improve the model’s generalization performance and train better representation. However, it relies heavily on human experience or intuition. The ML/DL community has recognized this problem and has been making efforts to find ways to effectively perform […]
2025-09-30 -
Case Study: Enhancing Quality Control in Rechargeable Battery Manufacturing with SAIGE VISION
Introduction Quality control (QC) is a critical phase in the product development lifecycle, serving as the final opportunity to identify and eliminate defects. Among the various QC methods, vision inspection —- focused on detecting visual defects -— plays a pivotal role. Traditionally reliant on human inspection, this step is now increasingly augmented by advanced technologies […]
2024-02-15 -
SAIGE VIMS: Real-Time Intelligent Video Monitoring for EV Rechargeable Battery Production
Introduction Ensuring the highest standards of product quality and safety in rechargeable battery manufacturing requires more than pre-delivery inspections; the underlying root causes of all defects that occur during production must be identified and addressed. To achieve this, manufacturing processes increasingly rely on facility monitoring systems. Prompt detection and response to issues in manufacturing and […]
2024-02-15