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

Elucidation of the phenotypic spectrum and genetic landscape in primary and secondary microcephaly

Purpose: Microcephaly is a sign of many genetic conditions but has been rarely systematically evaluated. We therefore comprehensively studied the clinical and genetic landscape of an unselected cohort of patients with microcephaly. Methods: We performed clinical assessment, high-resolution chromosomal microarray analysis, exome sequencing, and functional studies in 62 patients (58% with primary microcephaly [PM], 27% with secondary microcephaly [SM], and 15% of unknown onset). Results: We found severity of developmental delay/intellectual disability correlating with severity of microcephaly in PM, but not SM. We detected causative variants in 48.4% of patients and found divergent inheritance and variant pattern for PM (mainly recessive and likely gene-disrupting [LGD]) versus SM (all dominant de novo and evenly LGD or missense). While centrosome-related pathways were solely identified in PM, transcriptional regulation was the most frequently affected pathway in both SM and PM. Unexpectedly, we found causative variants in different mitochondria-related genes accounting for ~5% of patients, which emphasizes their role even in syndromic PM. Additionally, we delineated novel candidate genes involved in centrosome-related pathway (SPAG5, TEDC1), Wnt signaling (VPS26A, ZNRF3), and RNA trafficking (DDX1). Conclusion: Our findings enable improved evaluation and genetic counseling of PM and SM patients and further elucidate microcephaly pathways

Cooperative N-Boundary Tracking in Large Scale Environments

Abstract — Monitoring in large scale environments is a typical mission in cooperative robotics. This task requires the exploration of a huge domain by a generally small number of sensor equipped mobile robots. As time restrictions prohibit an exhaustive global search, a sampling strategy is required that allows an efficient spatial mapping of the environment. This paper proposes an adaptive sampling strategy for efficient simultaneous tracking of multiple concentration levels of an atmospheric plume by a team of cooperating unmanned aerial vehicles (UAVs). The approach combines uncertainty and correlation-based concentration estimates to generate sampling points based on already gathered data. The adaptive generation of sampling locations is coupled to a distributed modelpredictive controller for planning optimal vehicle trajectories under collision and communication constraints. Simulation results demonstrate that connectivity of all involved vehicles can be maintained and an accurate reconstruction of the plume is obtained efficiently. I

Demonstration-scale enzymatic saccharification of sulfite-pulped spruce with addition of hydrogen peroxide for LPMO activation

The saccharification of lignocellulosic materials like Norway spruce is challenging due to the recalcitrant nature of the biomass, and it requires optimized and efficient pretreatment and enzymatic hydrolysis processes to make it industrially feasible. In this study, we report successful enzymatic saccharification of sulfite-pulped spruce (Borregaard's BALI™ process) at demonstration scale, achieved through the controlled delivery of hydrogen peroxide (H2O2) for the activation of lytic polysaccharide monooxygenases (LPMOs) present in the cellulolytic enzyme preparation. We achieved 85% saccharification yield in 4 days using industrially relevant conditions – that is, an enzyme dose of 4% (w/w dry matter of substrate) of the commercial cellulase cocktail Cellic CTec3 and a substrate loading of 12% (w/w). Addition of H2O2 and the resulting controlled and high LPMO activity had a positive effect on the rate of saccharification and the final sugar titer. Clearly, the high LPMO activity was dependent on feeding the reactors with the LPMO co-substrate H2O2, as in situ generation of H2O2 from molecular oxygen was limited. These demonstration-scale experiments provide a solid basis for the use of H2O2 to improve enzymatic saccharification of lignocellulosic biomass at large industrial scale

Enzymatic degradation of sulfite-pulped softwoods and the role of LPMOs

Abstract Background Recent advances in the development of enzyme cocktails for degradation of lignocellulosic biomass, especially the discovery of lytic polysaccharide monooxygenases (LPMOs), have opened new perspectives for process design and optimization. Softwood biomass is an abundant resource in many parts of the world, including Scandinavia, but efficient pretreatment and subsequent enzymatic hydrolysis of softwoods are challenging. Sulfite pulping-based pretreatments, such as in the BALI™ process, yield substrates that are relatively easy to degrade. We have assessed how process conditions affect the efficiency of modern cellulase preparations in processing of such substrates. Results We show that efficient degradation of sulfite-pulped softwoods with modern, LPMO-containing cellulase preparations requires the use of conditions that promote LPMO activity, notably the presence of molecular oxygen and sufficient reducing power. Under LPMO activity-promoting conditions, glucan conversion after 48-h incubation with Cellic® CTec3 reached 73.7 and 84.3% for Norway spruce and loblolly pine, respectively, at an enzyme loading of 8 mg/g of glucan. The presence of free sulfite ions had a negative effect on hydrolysis efficiency. Lignosulfonates, produced from lignin during sulfite pretreatment, showed a potential to activate LPMOs. Spiking of Celluclast®, a cellulase cocktail with low LPMO activity, with monocomponent cellulases or an LPMO showed that the addition of the LPMO was clearly more beneficial than the addition of any classical cellulase. Addition of the LPMO in reactions with spruce increased the saccharification yield from approximately 60% to the levels obtained with Cellic® CTec3. Conclusions In this study, we have demonstrated the importance of LPMOs for efficient enzymatic degradation of sulfite-pulped softwood. We have also shown that to exploit the full potential of LPMO-rich cellulase preparations, conditions promoting LPMO activity, in particular the presence of oxygen and reducing equivalents are necessary, as is removal of residual sulfite from the pretreatment step. The use of lignosulfonates as reductants may reduce the costs related to the addition of small molecule reductants in sulfite pretreatment-based biorefineries