Analyzing Health Conditions of Critical Lift Components with the Use of AI-Assisted Image Analytics

I&T Solution Analyzing Health Conditions of Critical Lift Components with the Use of AI-Assisted Image Analytics
(REF: S-1363)
Trial Project
Solution Feature
  • Applying data augmentation technique to learn different variations of the same image, which can improve its performance.
  • Use active learning to reduce the burden of manual data labeling by selecting the most informative images for labeling.
  • Use Synthetic Data create additional training images that are not part of the original dataset when dealing with limited training data.
  • Applying Pseudo Labeling (Semi-supervised learning) to help improve the model's performance.
Trial Application and Expected Outcome
  • Trained AI model that can accurately classify the site photos into 12 specific components or exceptions
  • Trained AI model that can provide defect detection for 2 components (Suspension Rope and Brake)
  • Develop and fintune model with overall of 90% or above accuracy
  • Develop a scalable and adaptable AI model that can be applied new data for training and analysing via API
Info on I&T Solution Provider
Solution Provider:SOCIF LIMITED
Address:Unit 527, 5/F, 5W Enterprise Place, Phase 1 Hong Kong Science Park, Pak Shek Kok, NT, HK
Contact Person:Jason Yuen
Position:Chief Executive Officer
Tel:96649906
Email: jason.yuen@socif.co

For details of the above I&T solution, please contact the I&T solution provider.