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Titlebook: Artificial Intelligence and Soft Computing; 20th International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2021

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Integrate-and-Fire Neurons for Low-Powered Pattern Recognition series RC circuits, we developed a trainable neuron model that can be expressed in a recurrent form. Finally, we trained its simulation with an artificially generated dataset of dog postures and implemented it as hardware that showed promising energetic properties.
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Impact of ELM Parameters and Investment Horizon for Currency Exchange Predictionnd good quality forecasts for two out of three currency pairs was obtained in the study. The article also presents the relationship between the results generated by the neural network and the settings of these networks - in particular, the impact of the number of delays on forecast errors and the nu
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Applying Machine Learning Techniques to Identify Damaged Potatoes in gray gradation and the other in inverted color..The algorithm was implemented using the OpenCV library in Python. Testing was carried out in conditions close to the conditions of potato storage at vegetable bases..The percentage of properly-recognized damaged tubers was 92,1%.
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Quantifying the Severity of Common Rust in Maize Using Mask R-CNNrithms and the Mask R-CNN were evaluated on a real-world dataset created from images of maize leaves grown in a greenhouse. The Mask R-CNN was found to outperform the standard image processing algorithms in terms of counting the number of pustules, calculation of the pustule surface area and the ave
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Canine Behavior Interpretation Framework Using Deep Graph Modele dog posture in frame units, using a machine learning model based on the position information of the dog’s body part in the video captured by the camera. We then analyze dog behavior using graph models that define interrelationships among classified dog postures. We expect that our approach will help non-expertise to understand dog behavior.
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Efficient Recurrent Neural Network Architecture for Musical Style Transfereling of the music components. The proposed architecture allowed us to improve upon the state of the art solutions in terms of efficiency and range of applications while achieving high precision of the network.
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