Tree Automata Help One To Solve Equational Formulae In AC-Theories

this paper we consider particular equational formulae where equality =AC is the congruence induced by a set of associative-commutative axioms. The formulae we are interested in have the form t 6= AC t 1 : : : t 6= AC t n and are usually known as complement problems. To solve a complement problem is to find an instance of t which is not an instance of any t i modulo associativity-commutativity. We give a decision procedure based on tree automata which solves these formulae when all the t

Learning to detect, localize and recognize many text objects in document images from few examples

International audienceThe current trend in object detection and localization is to learn predictions with high capacity deep neural networks trained on a very large amount of annotated data and using a high amount of processing power. In this work, we particularly target the detection of text in document images and we propose a new neural model which directly predicts object coordinates. The particularity of our contribution lies in the local computations of predictions with a new form of local parameter sharing which keeps the overall amount of trainable parameters low. Key components of the model are spatial 2D-LSTM recurrent layers which convey contextual information between the regions of the image. We show that this model is more powerful than the state of the art in applications where training data are not as abundant as in the classical configuration of natural images and Imagenet/Pascal-VOC tasks. The proposed model also facilitates the detection of many objects in a single image and can deal with inputs of variable sizes without resizing. To enhance the localization precision of the coordinate regressor, we limit the amount of information produced by the local model components and propose two different regression strategies: (i) separately predict lower-left and upper-right corners of each object bounding box, followed by combinatorial pairing; (ii) only predict the left side of the objects and estimate the right position jointly with text recognition. These strategies lead to good full-page text recognition results in heterogeneous documents. Experiments have been performed on a document analysis task, the localization of the text lines in the Maurdor dataset

A mediterranean japonica rice (Oryza sativa) cultivar improvement through anther culture.

Certified seed producers systematically select and propagate registered varieties year after year in order to maintain their uniformity and the original registered cultivar traits. However, natural mutations, spontaneous breeding between varieties and alien grain contamination can introduce undesir- able variability. NRVC 980385 is a temperate japonica rice cultivar (Oryza sativa ssp. japonica) first regis- tered in Spain in 2002. In 2005 certification tests detected a plot differing from the original traits in terms of uniformity and height suggesting the pres- ence of a certain heterozygosis. This material was therefore seen as an opportunity to obtain newly stabilized doubled haploid (DH) lines which could compete in the Spanish short grain seed market. In this study, an in vitro anther culture protocol is defined which also covers the field tests selection to obtain four new, improved and stabilized DH derived lines ready to be registered for commercial proposes. This took just 4 years from the initial anther collection until new lines were grown in large scale field trials. Consequently, this protocol reduces the time for obtaining field assessed DH lines thereby having considerable advantages over other techniques by both maintaining the original registered cultivars and/or generating new derived varieties