Recovering Homography from Camera Captured Documents using Convolutional Neural Networks

Removing perspective distortion from hand held camera captured document images is one of the primitive tasks in document analysis, but unfortunately, no such method exists that can reliably remove the perspective distortion from document images automatically. In this paper, we propose a convolutional neural network based method for recovering homography from hand-held camera captured documents. Our proposed method works independent of document's underlying content and is trained end-to-end in a fully automatic way. Specifically, this paper makes following three contributions: Firstly, we introduce a large scale synthetic dataset for recovering homography from documents images captured under different geometric and photometric transformations; secondly, we show that a generic convolutional neural network based architecture can be successfully used for regressing the corners positions of documents captured under wild settings; thirdly, we show that L1 loss can be reliably used for corners regression. Our proposed method gives state-of-the-art performance on the tested datasets, and has potential to become an integral part of document analysis pipeline.Comment: 10 pages, 8 figure

Feasibility studies for the measurement of time-like proton electromagnetic form factors from p¯ p→ μ+μ- at P ¯ ANDA at FAIR

This paper reports on Monte Carlo simulation results for future measurements of the moduli of time-like proton electromagnetic form factors, | GE| and | GM| , using the p¯ p→ μ+μ- reaction at P ¯ ANDA (FAIR). The electromagnetic form factors are fundamental quantities parameterizing the electric and magnetic structure of hadrons. This work estimates the statistical and total accuracy with which the form factors can be measured at P ¯ ANDA , using an analysis of simulated data within the PandaRoot software framework. The most crucial background channel is p¯ p→ π+π-, due to the very similar behavior of muons and pions in the detector. The suppression factors are evaluated for this and all other relevant background channels at different values of antiproton beam momentum. The signal/background separation is based on a multivariate analysis, using the Boosted Decision Trees method. An expected background subtraction is included in this study, based on realistic angular distributions of the background contribution. Systematic uncertainties are considered and the relative total uncertainties of the form factor measurements are presented

The Crowdsourced Replication Initiative: Investigating Immigration and Social Policy Preferences. Executive Report.

In an era of mass migration, social scientists, populist parties and social movements raise concerns over the future of immigration-destination societies. What impacts does this have on policy and social solidarity? Comparative cross-national research, relying mostly on secondary data, has findings in different directions. There is a threat of selective model reporting and lack of replicability. The heterogeneity of countries obscures attempts to clearly define data-generating models. P-hacking and HARKing lurk among standard research practices in this area.This project employs crowdsourcing to address these issues. It draws on replication, deliberation, meta-analysis and harnessing the power of many minds at once. The Crowdsourced Replication Initiative carries two main goals, (a) to better investigate the linkage between immigration and social policy preferences across countries, and (b) to develop crowdsourcing as a social science method. The Executive Report provides short reviews of the area of social policy preferences and immigration, and the methods and impetus behind crowdsourcing plus a description of the entire project. Three main areas of findings will appear in three papers, that are registered as PAPs or in process

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty

This study explores how researchers’ analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers’ expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team’s workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers’ results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings

Smart Mobility Meets Industry: Enhancing Energy Flexibility Potentials by Combining Industrial Production & Electric Vehicle Charging

peer reviewedThe increasing share of renewable energy sources poses the challenge of volatile energy generation, requiring demand side management (DSM) to manage such volatility. In view of the high industrial electricity demand and the increasing charging demand of electric vehicles (EVs), both industry and mobility represent relevant areas of DSM. However, the combination of EV charging and energy-intensive industrial processes still contains untapped synergy potentials. Thus, we present a mixed-integer linear program and quantify the economic and ecologic potential of combining energy flexibilities of industry and electric mobility within a case study. For our evaluation, we compare the results of our model to a benchmark case that separately manages industry and EV flexibilities. Our findings suggest that implementing our approach would yield both economic and ecological benefits, resulting in a reduction in anticipated costs and emissions, as well as a decrease in associated uncertainty.9. Industry, innovation and infrastructur

Smart Mobility Meets Industry: Enhancing Energy Flexibility Potentials by Combining Industrial Production & Electric Vehicle Charging

The increasing share of renewable energy sources poses the challenge of volatile energy generation, requiring demand side management (DSM) to manage such volatility. In view of the high industrial electricity demand and the increasing charging demand of electric vehicles (EVs), both industry and mobility represent relevant areas of DSM. However, the combination of EV charging and energy-intensive industrial processes still contains untapped synergy potentials. Thus, we present a mixed-integer linear program and quantify the economic and ecologic potential of combining energy flexibilities of industry and electric mobility within a case study. For our evaluation, we compare the results of our model to a benchmark case that separately manages industry and EV flexibilities. Our findings suggest that implementing our approach would yield both economic and ecological benefits, resulting in a reduction in anticipated costs and emissions, as well as a decrease in associated uncertainty

Improved One-Pot Synthesis of Mixed Methyl−Aryl Platinum(II) Diimine Complexes

A general one-pot synthetic route for mixed methyl−aryl Pt(II) diimine complexes is described. Performing the alkylation in neat Me_2S instead of ether or THF greatly reduces the amount of comproportionation products otherwise formed, diminishes separation problems, and improves yields. Treatment of the intermediate methyl−aryl complexes (Me_2S)_2Pt(Me)(Ar) with diimines (N−N) furnishes the methyl−aryl Pt(II) diimine complexes (N−N)Pt(Me)(Ar) in 76−84% yields. The Pt methyl−phenyl complex [p-Tol-N ═ VC(Me)C(Me) ═ N-p-Tol]Pt(Me)(Ph) has been characterized by X-ray diffraction