Implemented machine vision quality inspection system for iron cast engine blocks using advanced deep learning algorithms. The system achieved 99.5% accuracy in defect detection.

Integrated smart cameras to automatically check label quality and verify correct date codes on packaging lines. System ensures 100% compliance with regulatory requirements.

Developed automated inspection system for PCBA components using robotic systems with integrated machine vision for high-precision component verification and placement validation.

Accurately counting the number of vials is challenging due to the disorganized and uneven stacking of the vials within the box. Traditional image processing methods would struggle because of the variations in lighting, shadows, and the occlusion of many vials by others.

However, an AI-based deep learning object detection vision tool can overcome these difficulties. The model, trained on a dataset of similar images, learns to identify the distinct features of a vial regardless of its position, lighting, or partial obstruction. 

This approach demonstrates the power of AI in solving complex computer vision problems that are beyond the capabilities of conventional methods