<b>German Style Number Plate Font Dataset for Text Recognition from Image</b>

Dataset Metadata<b>Title: Alphanumeric Character Recognition Dataset</b>Dataset ImageDescription:This dataset contains images of alphanumeric characters (0-9 and a-z) for text recognition tasks. Each character is represented by 100 samples, resulting in a total of 3600 samples. The images are grayscale with a resolution of 20x20 pixels, which have been flattened into 400-dimensional vectors.Content:<b>X:</b> The feature matrix with dimensions (3600, 400). Each row corresponds to a 20x20 pixel image flattened into a 400-dimensional vector.<b>y:</b> The label matrix with dimensions (3600, 36). Labels are one-hot encoded for 36 classes (0-9 and a-z), where each class has 100 samples.Features:<b>X (3600, 400):</b>Each row represents a flattened 20x20 pixel grayscale image of an alphanumeric character.Contains 3600 samples, with each sample having 400 features.<b>y (3600, 36):</b>Each row represents the one-hot encoded label for the corresponding sample in X.Contains 3600 samples, with each sample having 36 features representing the alphanumeric classes (0-9 and a-z).Classes:<b>36 classes</b> representing the alphanumeric characters:<b>Digits:</b> 0, 1, 2, 3, 4, 5, 6, 7, 8, 9<b>Letters:</b> a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, zUsage:This Dataset is primarily made for <b>"Pakistan (Punjab) Number Plates Recognition specifically for German-style number plate font "</b> but it is not limited, it is suitable for tasks such as:<br>Alphanumeric character recognitionOptical character recognition (OCR)Machine learning and deep learning experiments for text classificationSource:This dataset was created for research and educational purposes to facilitate the development and evaluation of text recognition algorithms.Acknowledgements:If you use this dataset in your research or projects, please cite the source appropriately.NOTESimply load csv files mentioned below for loading data in dataframes<b>X_NPRS_dataset_samples.csv</b><b>y_NPRS_dataset_labels.csv</b>or load <b>AlphaNumaric.mat</b> for loading data in <b>MATLAB</b>