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Text localization from scene images is a challenging task that finds application in many areas. In this work, we propose a novel hybrid text localization approach that exploits Multi-resolution Maximally Stable Extremal Regions to discard false-positive detections from the text confidence maps generated by a Fast Feature Pyramid based sliding window(More)
The focus of this study is the introduction of the construct of Human Mental Workload (HMW) in Web design, aimed at supporting current interaction design practices. An experiment has been conducted using the original Wikipedia and Google web-interfaces, and using two slightly different versions. Three subjective psychological mental workload assessment(More)
Predicting the future has been an aspiration of humans since the beginning of time. Today, predicting both macro-and micro-economic events is an important activity enabling better policy and the potential for profits. In this work, we present a novel method for automatically extracting forward looking-statement from a specific type of formal corporate(More)
BACKGROUND The high numbers of heterotrophic microorganisms that have been cultured from dental unit waterlines (DUWs) have raised concern that this water may exceed suggested limits for heterotrophic plate counts (HPCs). The main purpose of this investigation was to examine HPC variability in DUWs and to examine in detail the effect of laboratory(More)
In this work we propose a novel method for automatic gas meter reading from real world images. In a wide range of countries all over the world, the existing automatic technology is not adopted, usually the reading is manually done on site, and a picture is taken through a mobile device as a proof of reading. In order to confirm the reading, a tedious work(More)
In this paper we introduce a novel document image classification method based on combined visual and textual information. The proposed algorithm's pipeline is inspired to the ones of other recent state-of-the-art methods which perform document image classification using Convolutional Neural Networks. The main addition of our work is the introduction of a(More)
In this manuscript we propose a novel method for jointly page stream segmentation and multi-page document classification.The end goal is to classify a stream of pages as belonging to different classes of documents. We take advantage of the recent state-of-the-art results achieved using deep architectures in related fields such as document image(More)
The rise of online shopping has hurt physical retailers, which struggle to persuade customers to buy products in physical stores rather than online. Marketing flyers are a great mean to increase the visibility of physical retailers, but the unstructured offers appearing in those documents cannot be easily compared with similar online deals, making it hard(More)