“…Full architecture and training details are included in the scripts available for each dataset in GitHub. 10 As previously discussed, for a given text line image, a trained CRNN estimates a sequence of character posterior probability vectors (often referred to as "ConfMat"). While raw images can be directly accepted as input, results can often be improved if images are previously deskewed, deslanted, cleaned, contrast-enhanced, and/or size-normalized [15,16,17,18].…”