Computer Vision News 38 Challenges in Medical AI Development Working with the expertise of RSIP Vision enables us to mitigate this challenge in many ways. Our research and development team has implemented data augmentation tasks that are specific to each modality and application. Balancing datasets is an effective technique to optimize the training process. Let's consider a scenario where we obtain data from different sources. In such cases, we may have one source that has provided significantly more data than the others. If we train our network with this unbalanced data as a single block, the performance will be better on the larger dataset and not as good, or even very poor, on the smaller ones. Therefore, we need to balance the datasets. The data engineer must do this with great care, with the help of medical staff, to determine the best weight for each dataset while giving enough consideration to the smallest one. We have a technique for generating synthetic data, which involves creating new data by using available Ilya Kovler, CTO at RSIP Vision
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