Based on our own local language-based NLP engines, DDE’s customizable real-time social response analysis platform analyzes big data from outlets, such as news, blogs, communities, and social media, to show density of current issues, social attention attraction levels, sentiment analysis, degree of negativity and positivity, summarization, keyword and keyphrase, key context extraction, trace back to original sources, etc.

With our newest book spine detection system, users can easily participate in network inventory by taking pictures of their bookshelves and uploading them via their cell phones. The AI then identifies and catalogues the inventory from the uploaded images.

Originally developed to monitor fire escape safety distance in real-time, DDE’s Auto Distance and Route Calculation AI uses our object detection and image processing technologies to extract depth value from 2D images. Our Auto Distance and Route Calculation AI can be used with existing 2D security cameras to be further customised for client’s inventory and security system support, and can be applied to track objects and human movements and to send alerts when there is a security risk as part of security management.

Based on our highly precise camera recognition technologies, DDE’s camera-based unmanned store system detects everything in its view, including but not limited to people, pose, hand, product, basket, different motions of picking up and dropping of inventory, etc. Our unmanned store operating system can be operated with only a small number of cameras without any other sensors or equipment, providing an economic and easy business model for retail professionals.

DDE’s facial recognition technologies offer an economical and reliable solution for fast and accurate facial identification. Developed with the pandemic in mind, our facial recognition AI recognizes facial features even when wearing masks within milliseconds.

Developed using an advanced CPU-based model, instead of a GPU-based one, our facial recognition AI is economical and can be deployed with any existing cameras, equipment and systems.

Unlike rule-based self-driving systems, which require processing of numerous parameters for various environmental changes when modeling, that result in endless coding, DDE’s learning-based self-driving AI clones human driving behaviours in response to various road and environmental conditions with easily available driver behaviour data (i.e., steering angle, steering angular speed, velocity, etc.) from ECUs of existing vehicles and visual data from low-priced webcams.

Superior in both cost efficiency and performance, our self-driving AI does not require LiDAR or any other sensors and can operate in off-road and harsh weather conditions.

DDE’s multi-class defect inspection system combines and reduces existing DL models into unified models, reducing GPU usage by more than 90% on average as well as reduction in server and maintenance costs. Our defect inspection system is not only cost-efficient, but also highly accurate – having achieved 99.9% accuracy for our latest project.