Kasteev Museum Models and Dataset Iteration 1 & Iteration 2

The first iteration of the dataset of approximately 60 labeled images per class was created. The number of classes is 39. The second iteration of the dataset has limited sample size that led to insufficient recognition performance (~30% accuracy during in-museum testing). To address this, the dataset was augmented by repeating the same video processing methodology, resulting in an average of 120 images per class. This enhancement allowed the models to generalize better and significantly improved recognition accuracy (up to 96%).