A limited-size ensemble of homogeneous CNN/LSTMs for high-performance word classification
Table 3: Datasets.
['set', 'RIMES Image', 'RIMES Word', 'RIMES Word CI', 'KdK Image', 'KdK Word', 'KdK Word CI']
The first dataset is named RIMES, which was used to be comparable with the state-of-the-art methods. This database has different versions. We used isolated words of the version of ICDAR 2011 for evaluation of the methods and making the comparison with the published results possible Grosicki et al. The RIMES database is drawn from different types of handwritten manuscripts: postal mails and faxes. It contains 12,723 pages written by 1,300 volunteers using black ink on white paper. The RIMES dataset consists of 51,738 images of French handwriting for training, 7,464 images for validation and 7,776 images for testing. The dictionary size of the training set is 4,943 words, the validation set is 1,612 and the test set is 1,692, and the dictionary size of the whole dataset is 5,744 words. The comparison is accomplished case insensitive as it is common for the RIMES dataset, and the accent were contemplated. In the evaluation process of our model on RIMES, two dictionaries were used: Concise and Large. The Concise dictionary contains the whole words within the RIMES dataset, nwords = 5,744 (6K). A French dictionary called Large (50K) is used to study the effect of a larger dictionary.