Word Spotting In Handwritten Documents
1 papers with code • 0 benchmarks • 1 datasets
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Latest papers with no code
Bootstrapping Weakly Supervised Segmentation-free Word Spotting through HMM-based Alignment
In this paper, we propose an approach that utilises transcripts without bounding box annotations to train segmentation-free query-by-string word spotting models, given a partially trained model.
Attribute CNNs for Word Spotting in Handwritten Documents
By taking a probabilistic perspective on training CNNs, we derive two different loss functions for binary and real-valued word string embeddings.
Learning Deep Representations for Word Spotting Under Weak Supervision
Convolutional Neural Networks have made their mark in various fields of computer vision in recent years.