Deep Learning Data Requirements: Addressing Common Misconceptions

Thank you for your comment. You are correct that there are many publicly available datasets and trained models that can be used for deep learning-based solutions. Transfer learning, pseudolabeled, and synthesized datasets can also be effective in overcoming the issue of needing a large amount of data. Additionally, you are correct that deep learning models do not require as much memory during inference compared to training, and can be updated with new data without needing to be fully retrained. However, it is important to note that the quality and relevance of the data used for training and inference will still have a significant impact on the performance of the model.