We present a framework for learning an efficient holistic representation for handwritten word
images. The proposed method uses a deep convolutional neural network with traditional …

Word spotting has become a field of strong research interest in document image analysis
over the last years. Recently, AttributeSVMs were proposed which predict a binary attribute …

This thesis, first defines the goal of Keyword Spotting from a Decision Theory perspective.
Then, the problem is tackled following a probabilistic formulation. More precisely, Keyword …

Word spotting is a popular tool for supporting the first exploration of historic, handwritten
document collections. Today, the best performing methods rely on machine learning …

Word segmentation in documents is a critical stage towards word and character recognition,
as well as word spotting. Despite recent advancements in word segmentation and object …

In order to reduce energy consumption of Wireless Sensor Network nodes, a novel
compression algorithm based on the principle of Adaptive Huffman Code is proposed in the …

In this paper, we present a word spotting system in text lines for offline Indic scripts such as
Bangla (Bengali) and Devanagari. Recently, it was shown that the zone-wise recognition …

For easy accessibility of the information from the digitized document images, optical
character recognition (OCR)-based software can be used. But in the case of handwritten …

In the field of historical manuscript research, scholars frequently encounter novel symbols in
ancient texts, investing considerable effort in their identification and documentation …

The annotation-free word spotting method that is proposed in this paper makes document
images searchable without requiring any labeled training data. Thus, our method supports …