Document analysis at DFKI. - Part 1: Image analysis and text recognition

Document analysis is responsible for an essential progress in office automation. This paper is part of an overview about the combined research efforts in document analysis at the DFKI. Common to all document analysis projects is the global goal of providing a high level electronic representation of documents in terms of iconic, structural, textual, and semantic information. These symbolic document descriptions enable an "intelligent\u27; access to a document database. Currently there are three ongoing document analysis projects at DFKI: INCA, OMEGA, and PASCAL2000/PASCAL+. Though the projects pursue different goals in different application domains, they all share the same problems which have to be resolved with similar techniques. For that reason the activities in these projects are bundled to avoid redundant work. At DFKI we have divided the problem of document analysis into two main tasks, text recognition and text analysis, which themselves are divided into a set of subtasks. In a series of three research reports the work of the document analysis and office automation department at DFKI is presented. The first report discusses the problem of text recognition, the second that of text analysis. In a third report we describe our concept for a specialized document analysis knowledge representation language. The report in hand describes the activities dealing with the text recognition task. Text recognition covers the phase starting with capturing a document image up to identifying the written words. This comprises the following subtasks: preprocessing the pictorial information, segmenting into blocks, lines, words, and characters, classifying characters, and identifying the input words. For each subtask several competing solution algorithms, called specialists or knowledge sources, may exist. To efficiently control and organize these specialists an intelligent situation-based planning component is necessary, which is also described in this report. It should be mentioned that the planning component is also responsible to control the overall document analysis system instead of the text recognition phase onl

Effect of Apheresis for ABO and HLA Desensitization on Anti-Measles Antibody Titers in Renal Transplantation

Desensitization strategies for ABO-incompatible renal transplants with plasma exchange (PE) or specific immunoadsorption (IA) decrease immunoglobulin levels. After recent measles outbreak and decreasing vaccination rates, we studied the impact of apheresis on anti-measles antibodies. Anti-measles antibodies were measured before desensitization, before transplantation and during followup in 12 patients with ABO incompatibility (2x PE only, 8x IA only, and 2x IA and PE) and 3 patients with donor-specific HLA antibodies (all PE). Patients received rituximab, IVIG, and standard immunosuppressive therapy. All patients had detectable anti-measles antibodies before desensitization (mean 3238 mU/l, range 560–8100). After 3–6 PE sessions, titers decreased significantly to 1710 mU/l (P < 0.05), in one patient to nondetectable values, while IA only maintained protective titers. After a median followup of 64 days, anti-measles antibodies returned to baseline in all patients. Immunity against measles was temporarily reduced by apheresis but remained detectable in most patients at time of transplantation. Desensitization maintains long-term protective immunity against measles

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

MergeLayouts – Overcoming faulty segmentation by a comprehensive voting of commercial OCR devices

In this paper, we will present a comprehensive voting approach, taking entire layouts obtained from commercial OCR devices as input. Such a layout comprises segments of three kinds: lines, words, and characters. By combining all attributes of a segment (e.g. recognized text, font height etc.), we attain a “better ” layout, representing the original page layout as good as possible. The voting process itself is hierarchically organized, starting with the line segments. For each level, a search tree is spawn and all fellow segments (segments from different layouts which denote the same image area) are established. A heuristic search method is utilized which is guided by a similarity measure defined on segments. Deviations in the segmentation, as well as segmentation errors of individual commercial OC

MergeLayouts- a Comprehensive Voting of Commercial OCR Devices

Sophisticated voting techniques described in recent literature focused more or less on isolated voting of classification results. Most often, character or word classification results of different classifiers were combined to achieve more reliable results and to overcome a single classifier’s weaknesses. We will present a more comprehensive voting approach, taking entire layouts obtained from commercial OCR devices as input. Such a layout comprises segments of three kinds: lines, words, and characters, each of them comprising several attributes, e.g. recognized text, identified font height, coordinates within the original image etc. By combining all those attributes, we attain a “better ” layout, representing the original page layout as good as possible. The voting process itself is hierarchically organized, starting with the line segments. For each level, a search tree is spawn and all fellow segments (segments from different layouts, which denote the same image area) are established. Crucial to MergeLayouts is a similarity measure defined on segments, which allows for an efficient heuristic search process and which guarantees a reliable page layout retention

Innovative Business Models for Higher Education: An Exploratory Analysis on Education Technology Start-Ups in Selected Countries

There have not been any (breakthrough) innovations in education in the past 100 years. We mostly teach and learn the same way as our ancestors have done and there haven’t yet been any innovations that allow for faster or better learning or teaching. As a result there is a growing need for enhanced education technology (edtech) in the field of education. As innovation often comes from startups, this article examines which innovative business models are developed outside higher education institutions (in the edtech field), especially by entrepreneurs. Previous research has discussed the need for edtech innovation in educational institutions and has given concrete examples of how to improve present higher education models, technologies and procedures. Yet, only a few studies have analysed and compared edtech firms between different countries. The goal of this study is to analyse the core elements of innovative business models in the field of edtech start-ups in higher education and to identify the most original practices in teaching and learning. Our analysis of innovative business models in the edtech sector may inform higher education institutions about how to address their future challenges, for instance, by cooperating with edtech companies