Warren, MI, US
Project Engineers:
Develop and optimize a deep learning-based defect detection system for electrode defects using the YOLO algorithm, integrating attention mechanisms and additional detection layers for high-precision on tiny defect detection.
Design custom image segmentation and stitching algorithm, improving defect localization and real-time quality control.
Build GUI-based visualization software via PyQt for interactive defect analysis, supporting ROI (region of interest) marking, dynamic scaling, defect result display and automated quality analysis reports generation.
Primary worksite is Plymouth MI but relocation possible.
Req: Master's degree in Mechanical or Electrical Engineering or related field. Ref: #115.
