I have been working on an image classification tasks for which I am extracting the image frames from the video stream collected for different classes.
I have already trained an image classification model (using transfer learning) however due to the outliers (or overlap in the class distribution) accuracy of the model is poor. And not able to generalize the new images / video streams.
Could you please help me with the below queries
How the sample is distributed in each class ? Can I use any visualization techniques (for example : histogram) to see the sample distribution.
And also going through the image one by one is tedious process so is there a technique with which I can find the outliers (outlier images) from the samples. So that I can remove outliers before training the model.
Any updates on this..