Deep learning models using locally and globally annotated training images

A system comprising:

• a memory;
• and
• a processor in communication with the memory, the processor being configured to perform operations comprising:
• receiving training images;
• utilizing one or more AI models that each analyze the training images, wherein the one or more AI models include respective objective functions;
• receiving, from the one or more AI models, the respective objective functions obtained after each of the one or more AI models are separately trained;
• and
• submitting a combined weighted objective function to train the AI system, wherein the combined weighted objective function is a weighted combination of the respective objective function from each of the one or more AI models.

A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform operations, the operations comprising:

• receiving training images;
• utilizing one or more AI models that each analyze the training images, wherein the one or more AI models include respective objective functions;
• receiving, from the one or more AI models, the respective objective functions obtained after each of the one or more AI models are separately trained;
• and
• submitting a combined weighted objective function to train the AI system, wherein the combined weighted objective function is a weighted combination of the respective objective function from each of the one or more AI models.