8,249 research outputs found
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition
Recognizing irregular text in natural scene images is challenging due to the
large variance in text appearance, such as curvature, orientation and
distortion. Most existing approaches rely heavily on sophisticated model
designs and/or extra fine-grained annotations, which, to some extent, increase
the difficulty in algorithm implementation and data collection. In this work,
we propose an easy-to-implement strong baseline for irregular scene text
recognition, using off-the-shelf neural network components and only word-level
annotations. It is composed of a -layer ResNet, an LSTM-based
encoder-decoder framework and a 2-dimensional attention module. Despite its
simplicity, the proposed method is robust and achieves state-of-the-art
performance on both regular and irregular scene text recognition benchmarks.
Code is available at: https://tinyurl.com/ShowAttendReadComment: Accepted to Proc. AAAI Conference on Artificial Intelligence 201
New Negentropy Optimization Schemes for Blind Signal Extraction of Complex Valued Sources
Blind signal extraction, a hot issue in the field of communication signal processing, aims to retrieve the sources through the optimization of contrast functions. Many contrasts based on higher-order statistics such as kurtosis, usually behave sensitive to outliers. Thus, to achieve robust results, nonlinear functions are utilized as contrasts to approximate the negentropy criterion, which is also a classical metric for non-Gaussianity. However, existing methods generally have a high computational cost, hence leading us to address the problem of efficient optimization of contrast function. More precisely, we design a novel “reference-based” contrast function based on negentropy approximations, and then propose a new family of algorithms (Alg.1 and Alg.2) to maximize it. Simulations confirm the convergence of our method to a separating solution, which is also analyzed in theory. We also validate the theoretic complexity analysis that Alg.2 has a much lower computational cost than Alg.1 and existing optimization methods based on negentropy criterion. Finally, experiments for the separation of single sideband signals illustrate that our method has good prospects in real-world applications
3,3′-(p-Phenylenedimethylene)diimidazol-1-ium bis(3-carboxy-4-hydroxybenzenesulfonate) dihydrate
In the title compound, C14H16N4
2+·2C7H5O6S−·2H2O, the 3,3′-(p-phenylenedimethylene)diimidazol-1-ium dication lies on a crystallographic inversion center. In the crystal structure, dications, anions and solvent water molecules are linked via O—H⋯O, N—H⋯O and C—H⋯O hydrogen bonds, and C—H⋯π interactions, forming a three-dimensional network containing R
2
2(4), R
2
4(12), R
4
4(22), R
8
10(32) and R
12
14(66) ring motifs
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