Titlebook: Reproducible Research in Pattern Recognition; Second International Bertrand Kerautret,Miguel Colom,Hugues Talbot Conference proceedings 201

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Discrete Regular Polygons for Digital Shape Rigid Motion via Polygonizationt whose boundary is not necessarily differentiable. Under this condition, a rigid motion scheme for digital objects of . is proposed to guarantee that a well-composed object will remain well-composed, and its global geometry will be approximately preserved. In this paper, we are interested in polygo

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Non-deterministic Behavior of Ranking-Based Metrics When Evaluating Embeddingsnce metrics become ambiguous. In this paper, we present an analysis of the ambiguity quantized distances introduce and provide bounds on the effect. We demonstrate that it can have a measurable effect in empirical data in state-of-the-art systems. We also approach the phenomenon from a computer secu

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CNN Implementation for Semantic Heads Segmentation Using Top-View Depth Data in Crowded Environmentk and detect people in cases of heavy occlusions based on CNNs for semantic segmentation using top-view RGB-D visual data. The purpose is the design of a novel U-Net architecture, U-Net 3, that has been modified compared to the previous ones at the end of each layer. In order to evaluate this new ar

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On the Implementation of ALFA – Agglomerative Late Fusion Algorithm for Object Detectiontor predictions while taking into account bounding box locations and class scores. We discuss the source code of ALFA and another late fusion algorithm – Dynamic Belief Fusion (DBF). The workflow and the hyperparameters necessary to reproduce the published results are presented. We also provide a fr

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On Reproducibility of Deep Convolutional Neural Networks Approachesible, it is necessary to consider the reproducibility of these models both at training and inference time. With the introduction of Deep Learning (DL), the assessment of reproducibility became a critical issue due to heuristic considerations made at training time that, although improving the optimiz

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Some Comments on Variational Bayes Block Sparse Modeling with Correlated Entriesblocks are correlated. In particular, the effect of the threshold to prune out variance parameters of algorithms corresponding to several choices of marginals, viz. multivariate Jeffery prior, multivariate Laplace distribution and multivariate Student’s t distribution, is discussed. We also provide

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An Image Processing Library in Modern C++: Getting Simplicity and Efficiency with Generic Programminefficient and production-quality algorithms, some may look for a large tool set, while others may look for extensibility and genericity to inter-operate with their own code base...but in most cases, they want a simple-to-use and stable product. For a C++ Image Processing library designer, it is diff

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New Definition of Quality-Scale Robustness for Image Processing Algorithms, with Generalized Uncertawpoints. Actually, the robustness models the capacity of a computerized approach to resist to perturbing phenomena and data uncertainties, and generate common artefact while designing algorithms. However, this question has not been dealt in depth in such a way for image processing tasks. In this art

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ReScience C: A Journal for Reproducible Replications in Computational Scienceentation of the methods described in the original article by a different team of researchers. Replication is often performed by scientists who wish to gain a better understanding of a published method, but its results are rarely made public. ReScience C is a peer-reviewed journal dedicated to the pu

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rtschaft drastisch vor Augen fUhrte. Manche positive Globalisierungstendenz, wie die fortschreitende Liberali­ sierung und Integration des Welthandels oder der zunehmende in­ ternationale Konsens uber die Notwendigkeit einer nachhaltigen Entwicklung ("Sustainable Development"), hat unter den kurzfri