Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers
Table 4: Results of the first series of experiments reported as mean values ± standard deviation computed from 10 runs. Stars indicate statistically significant improvements from Text and Image+Text relative to Image.
['[BOLD] Metric', '[BOLD] Modality', '[BOLD] Serial', '[BOLD] Weather', '[BOLD] Death Notice', '[BOLD] Stocks', '[BOLD] Average']
In general, the Image model outperforms the pure Text model by a large margin in terms of mIoU and precision. Except for recall-oriented setups, there is no advantage of restricting the models to textual features only. As expected, Image model is stronger on classes that are more visually distinct ( Weather and Stocks) than on classes that are mainly text based (Serial and Death notice).