Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Lower Benefits to the Refugees in Denmark: Missing Recognition?

This article is a study of the contrast between the Danish law concerning reduced economic benefits for newly arrived refugees and immigrants (known as Start Help or as introductory benefit) and the idea of recognition as the condition for individual self-realization and justice. Our assumption is that Start Help both implies economic discrimination against newly arrived persons in Denmark (especially refugees and their families under family reunification rules) and symbolizes a lack of recognition. We have chosen to adopt the theories of recognition (and redistribution) propounded by Axel Honneth and Nancy Fraser to explore our queries about Start Help and the discriminatory impact on its recipients. Empirically the article is based on in-depth qualitative interviews with six refugees who all receive Start Help.

Understanding the Other’s “Understanding” of Violence: Legitimacy, Recognition, and the Challenge of Dealing with the Past in Divided Societies

Post-conflict societies which have achieved a cessation of violence and embarked on a political conflict transformation process cannot in the long-term avoid a process of dealing with the past. Case studies of South Africa and Northern Ireland confirm this normative claim, showing that within the post-war society as a whole a social consensus on how to “understand” and “recognize” the use of violence that occurred during the conflict is necessary: understanding the other’s “understanding” of violence. A mutual understanding must be reached that both sides fought a campaign that was just and legitimate from their own perspective. The morality of the “other’s violence” has to be recognized.

Analysis of eye and head coordination in a visual peripheral recognition task

Coordinated eye and head movements simultaneously occur to scan the visual world for relevant targets. However, measuring both eye and head movements in experiments allowing natural head movements may be challenging. This paper provides an approach to study eye-head coordination: First, we demonstra- te the capabilities and limits of the eye-head tracking system used, and compare it to other technologies. Second, a beha- vioral task is introduced to invoke eye-head coordination. Third, a method is introduced to reconstruct signal loss in video- based oculography caused by cornea reflection artifacts in order to extend the tracking range. Finally, parameters of eye- head coordination are identified using EHCA (eye-head co- ordination analyzer), a MATLAB software which was developed to analyze eye-head shifts. To demonstrate the capabilities of the approach, a study with 11 healthy subjects was performed to investigate motion behavior. The approach presented here is discussed as an instrument to explore eye-head coordination, which may lead to further insights into attentional and motor symptoms of certain neurological or psychiatric diseases, e.g., schizophrenia.