This project aims to apply deep learning technology to retail inventory management. Using the latest object detection and classification algorithms, we can draw bounding boxes surrounding the retail products shown in an image. The sets of bounding boxes represent different products that are also training materials. The technology can help retailers to recognize stock keeping units, price compliance and share of shelf, which in turn assists them in making marketing decisions and improving their sales.
- Customer Flow Measurement
- Display Effectiveness
- Shopper Engagement
- Anti-thief System
- Shopping Recommendation
Similar applications have been developed by other deep learning models such as faster R-CNN, Mask R C-NN, and YOLO.
DLC is now seeking for any partnership for this project.