We find that additional data does help, but only with correct regularization and treatment of noisy examples or “outliers” in the training data.
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Is more training data better?
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How much data is needed for object detection?
Mar 5, 2015 · This paper investigates the question of whether existing detectors will continue to improve as data grows, or saturate in performance due to limited model ...
Much of the impressive progress in object detection is built on the methodologies of statistical machine learn- ing, which make use of large training datasets ...
We find that additional data does help, but only with correct regularization and treatment of noisy examples or "outliers" in the training data. Surprisingly, ...
Aug 11, 2023 · Depends on what you're trying to detect. I've had success with 50-100 images for some projects while some required 5000+.
This paper investigates the question of whether existing detectors will continue to improve as data grows, or saturate in performance due to limited model ...
It is conjecture that the greatest gains in detection performance will continue to derive from improved representations and learning algorithms that can ...
Jun 27, 2012 · They both show that adding more data always makes models better, while adding parameter complexity beyond the optimum, reduces model quality. If ...
We find that additional data does help, but only with correct regularization and treatment of noisy examples or “outliers” in the training data. Surprisingly, ...
Apr 10, 2022 · You need at least 100 images per class for training the object detection model. ... we can use more and more complex models without overfitting.