Titlebook: Reproducible Research in Pattern Recognition; Fourth International Bertrand Kerautret,Miguel Colom,Benjamin Perret Conference proceedings 2

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On Challenging Aspects of?Reproducibility in?Deep Anomaly Detectionng examples based on our work and present mitigation strategies. Furthermore, we document a trade-off between the complexity of experiments and the strength of the empirical evidence obtained through them, both of which impact different types of reproducibility. Ultimately, we argue that the reprodu

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Combining Max-Tree and?CNN for?Segmentation of?Cellular FIB-SEM Images relation between the binary components obtained at successive level-sets. Various attributes related to these binary components can be computed and stored into the tree..Max-trees have been involved in many applications, enabling to perform attribute filtering in an efficient algorithmic way. Since

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Automatic Forest Road Extraction from?LiDAR Data Using Convolutional Neural Networkstion from LiDAR data using deep learning approaches. For this, we use images computed from an interpolated surface, called . (DTM), of the 3D point cloud. In order to train and validate the neural network models, two ground truth datasets associated to DTM images are considered: (1) manual digitizat

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Promoting Reproducibility of?Research Results in?International Events (Report from?the?, RRPR)tion (ICPR), this paper reports the main discussions that were held during and after the workshop. In particular, the integration of reproducible research inside an international conference was the first main axis of reflection. Further discussions addressed the ways of initiating or imposing reprod

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Conference proceedings 2023ion, RRPR 2022, held in Montreal, Canada, in August 2022.. The 5 revised full papers presented together with 4 short papers, were carefully reviewed and selected from 9 submissions.. The papers were organized into three main categories

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