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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,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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Remote Learning of Mathematics for Visually Impaired Students During COVID-19: Exploring Online Intrises, social distancing, increases in food demand, job losses and closure of educational institutions. This led to a rapid transition from face-to-face to remote teaching. Most remote learning platforms are designed primarily for sighted students and are less useful for visually-impaired students.

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Optimization of Lacrimal Aspect Ratio for Explainable Eye Blinking, lacrimal area for detection. This paper proposes a new eye blinking detection method using a novel lacrimal aspect ratio (LAR) strategy that utilises eyebrow movement and eyes. The proposed algorithm estimates facial landmarks using an automatic facial landmark detector to extract a single scalar q

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SIM_RL: A New Approach for Integrating Simulation with Reinforcement Learning,ystem becomes more complex, the simulation engine must run numerous times in response to the increasing complexity of the input and the simulation process. Additionally, an expensive physical experiment needs to be performed to validate the results. This paper demonstrates an innovative, general-pur

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Grouping Shapley Value Feature Importances of Random Forests for Explainable Yield Prediction,a variety of yield prediction scenarios. The data included for the prediction of yields are intricate and the models are often difficult to understand. However, understanding the models can be simplified by using natural groupings of the input features. Grouping can be achieved, for example, by the