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Translated • Traditional Chinese

The Challenges and Transformation of the Traditional Recycling Industry

Published
Author
Jiun-Ling Wei
Data Annotation Team Leader

The recycling industry faces growing challenges from labor shortages and hazardous working conditions. AI-powered recycling offers a solution by automating sorting, improving efficiency, and enhancing worker safety. How will this technology transform the industry and drive sustainability?

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Translated • Traditional Chinese

AI Transforming Recycling: Paving the Way for a New Era of Sustainable Circulation

Published
Author
Chieh-Han Lee
CTO

Traditional recycling methods, reliant on manual labor and subjective judgment, struggle to meet the demands of modern waste management. With the rise of Artificial Intelligence (AI), the recycling process becomes more precise and efficient, driving the realization of a circular economy and creating lasting value for the planet's future.

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From Products to Waste: Synthetic Waste Data Generation with NVIDIA Omniverse

Published
Author
Rémi Pyronnet
Computer Vision Engineer

Traditional waste dataset collection has limitations, such as imbalanced data and labeling errors. AIRECO's synthetic data generation method addresses these challenges by using 3D models to simulate waste, improving data quality and scalability. Learn how this approach enhances AI training and reduces human effort.

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