In the research, they analyze the two challenges of learning from time series data with noisy labels: (a) Label noise in time ...

As industries globally inch closer to 2030, the labelling sector is at the crossroads of transformation and complexity. Driven by advancing technologies, evolving regulations, and growing consumer ...

Labeling data is an important part of the machine learning production process. It can be treated as an engineering and mathematical task that can be solved through technological means. Automation ...

Artificial intelligence and machine learning exist on the back of a lot ... of low-paid workers whose job it is to classify and label data - the lifeblood of such systems. But increasingly there ...