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Titlebook: Intelligent Systems and Applications; Proceedings of the 2 Kohei Arai Conference proceedings 2024 The Editor(s) (if applicable) and The Aut

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,Low Cost Machine Vision for Insect Classification,e for this is a systematic and up-scaled monitoring in order to detect correlations and identify countermeasures. Therefore, automatized monitoring using live traps is important, but so far there is no system that provides image data of sufficient detailed information for entomological classificatio
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Shared Intentionality Before Birth: Emulating a Model of Mother-Fetus Communication for Developing appearance of fetuses’ perception in intentional engagement with the environment. It means that fetuses are able to select the relevant stimulus from the noisy environment with a cacophony of other stimuli: chemical interactions, pressure changes, and electromagnetic fields. This ability can appear
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,On Object Detection Based on Similarity Measures from Digital Maps,nd. We will explore different similarity measures to compare the legend objects to those detected in different areas of the map. Our object detection method is evaluated on maps representing wastewater networks. In particular, we are interested in the detection of objects that represent lifting stat
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Virtualization of the Paint Mixing Process Using the Hardware in the Loop Technique,ndustrial process (software) and a programmable logic controller, PLC, (Hardware). The simulation section consists of TIA PORTAL for the automation of the paint mixing process, while the visualization and monitoring corresponding to the SCADA system is done with the INTOUCH software, and finally the
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Locally Enhanced Chan-Vese Model with Anisotropic Mesh Adaptation for Intensity Inhomogeneous Imagey. Many models have been proposed to address this difficulty. In this paper, we propose a locally enhanced Chan-Vese model (LECV) to successfully segment images with intensity inhomogeneity. We define a new signed pressure force (SPF) function based on the local image information from a triangular m
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