Deep Adaptive Learning for Writer Identification based on Single Handwritten Word Images

There are two types of information in each handwritten word image: explicit information which can be easily read or derived directly, such as lexical content or word length, and implicit attributes such as the author's identity. Whether features learned by a neural network for one task can be used for another task remains an open question. In this paper, we present a deep adaptive learning method for writer identification based on single-word images using multi-task learning. An auxiliary task is added to the training process to enforce the emergence of reusable features. Our proposed method transfers the benefits of the learned features of a convolutional neural network from an auxiliary task such as explicit content recognition to the main task of writer identification in a single procedure. Specifically, we propose a new adaptive convolutional layer to exploit the learned deep features. A multi-task neural network with one or several adaptive convolutional layers is trained end-to-end, to exploit robust generic features for a specific main task, i.e., writer identification. Three auxiliary tasks, corresponding to three explicit attributes of handwritten word images (lexical content, word length and character attributes), are evaluated. Experimental results on two benchmark datasets show that the proposed deep adaptive learning method can improve the performance of writer identification based on single-word images, compared to non-adaptive and simple linear-adaptive approaches.Comment: Under view of Pattern Recognitio

DeepOtsu: Document Enhancement and Binarization using Iterative Deep Learning

This paper presents a novel iterative deep learning framework and apply it for document enhancement and binarization. Unlike the traditional methods which predict the binary label of each pixel on the input image, we train the neural network to learn the degradations in document images and produce the uniform images of the degraded input images, which allows the network to refine the output iteratively. Two different iterative methods have been studied in this paper: recurrent refinement (RR) which uses the same trained neural network in each iteration for document enhancement and stacked refinement (SR) which uses a stack of different neural networks for iterative output refinement. Given the learned uniform and enhanced image, the binarization map can be easy to obtain by a global or local threshold. The experimental results on several public benchmark data sets show that our proposed methods provide a new clean version of the degraded image which is suitable for visualization and promising results of binarization using the global Otsu's threshold based on the enhanced images learned iteratively by the neural network.Comment: Accepted by Pattern Recognitio

On the Stable Relative Orientation of Groups Connected by a Carbon-Carbon Single Bond

Langseth and his co-workers [1] have recently applied the results of essentially incomplete spectroscopic studies of liquid cyclohexane, symmetrical tetrachloroethane, and ethylene deuterobromide to a discussion of the intramolecular forces restricting internal rotation about the C-C bond. We believe that none of their structural conclusions is correct. Their discussion is based on their conclusion that in these molecules the opposed or eclipse configurations are the stable ones. Insofar as liquid cyclohexane and symmetrical tetrachloroethane are concerned this conclusion is most probably incorrect since it directly contradicts the results of a great number of more straightforward studies of these and similar molecules

Studies on the denaturation of antibody. IV. The influence of pH and certain other factors on the rate of inactivation of Staphylococcus antitoxin in urea solutions

In previous work on the denaturation of antibody, studies have been made of some of the factors influencing the inactivation of diphtheria antitoxin in urea solutions (1, 2). A quantitative formulation of a simple kinetic theory was found to fit satisfactorily the experimental data and to offer a reasonable explanation of the deviation of the inactivation from simple first order behavior (2). In the present work we have studied the inactivation of Staphylococcus antitoxin, investigating the influence of certain new factors on the rate and course of the over-all reaction, with a view toward gaining further insight into the mechanism of the reactions, and reinvestigating the influence of pH, a factor studied previously with diphtheria antitoxin, in order to test the applicability of the proposed kinetic mechanism to different antibodies

Analysis of texture and connected-component contours for the automatic identification of writers

Recent advances in "off-line" writer identification allow for new applications in handwritten text retrieval from archives of scanned historical documents. This paper describes new algorithms for forensic or historical writer identification, using the contours of fragmented connected-components in free-style handwriting. The writer is considered to be characterized by a stochastic pattern generator, producing a family of character fragments (fraglets). Using a codebook of such fraglets from an independent training set, the probability distribution of fraglet contours was computed for an independent test set. Results revealed a high sensitivity of the fraglet histogram in identifying individual writers on the basis of a paragraph of text. Large-scale experiments on the optimal size of Kohonen maps of fraglet contours were performed, showing usable classification rates within a non-critical range of Kohonen map dimensions. The proposed automatic approach bridges the gap between image-statistics approaches and purely knowledge-based manual character-based methods

Sharia Law and the Transition Towards More Democracy and a Market Economy – Restrictions and Opportunities

The main source of Islamic Law, the Sharia, provides not only spiritual leadership for human beings, or guidelines how to practice the religion of Islam properly, but also includes normative implications for the design of the political and economic sphere of a state. Beyond the sheer scientific interest, these implications of Islam became relevant (again) in the context of the recent transition processes in the Middle East and North Africa. Despite not being finished yet, the transformations will raise new challenges for their perspective economies and the political systems as many religion-based parties (e.g. Al Nahda in Tunisia) become important (if not the leading) forces in their respective countries. While many empirical studies, based on sheer quantitative approaches, conclude that, in Muslim countries, democracy—and in a way market-oriented economic principles—is less developed, most of these approaches suffer from a relevant shortcoming. Indeed, these studies include countries with Muslim majorities and take them as a proxy for the influence of Islam on democracy or the development of a market economy. But this equation may be too easy. At least in modern national states with Muslim majorities, the principles of Sharia have almost never been applied (duly) when designing the political and economic system. Consequently, these analyses—in the best case—measure the biased effects of a “mixed influence” of Sharia Law and other societal or traditional factors on democracy and the shape and structure of the economy, but not the isolated effects of the Sharia Law. Our paper closes this gap, as we scrutinize the implications of Sharia Law in favor or against a democratic system (or transition towards it) and market-oriented economic system, focussing on the principles as laid down in the text per se. While Sharia Law is interpreted quite differently among Islamic scholars and groups, there are “core elements” which are more or less universally accepted among scholars and consequently are focused on in our work. First, we isolate the main lines of Sharia Law which may be relevant for the design of a political order or constitution as well as an economic system. Then, based on a triangulation approach, we examine how far the normative specifications in Sharia Law are coherent with the basics of democracy, namely separation of powers and judicial independence, rule of law, citizens’ rights, participation and accountability, and main principles of market economies, as competition and transparency. For that purpose, in addition to our theoretical analysis, we test empirically if the fact that a country has a Muslim majority makes it more prone towards a transition towards more democracy. A short summary and some policy recommendations close our paper