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Goutham Kallempudi, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker and Muhammad Zeshan Afzal
The graphical page object detection classifies and localizes objects such as Tables and Figures in a document. As deep learning techniques for object detection become increasingly successful, many supervised deep neural network-based methods have been in...
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Sankalp Sinha, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker and Muhammad Zeshan Afzal
In the age of deep learning, researchers have looked at domain adaptation under the pre-training and fine-tuning paradigm to leverage the gains in the natural image domain. These backbones and subsequent networks are designed for object detection in the ...
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Birhanu Belay, Tewodros Habtegebrial, Million Meshesha, Marcus Liwicki, Gebeyehu Belay and Didier Stricker
In this paper, we introduce an end-to-end Amharic text-line image recognition approach based on recurrent neural networks. Amharic is an indigenous Ethiopic script which follows a unique syllabic writing system adopted from an ancient Geez script. This s...
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