Titlebook: Artificial Intelligence and Soft Computing; 21st International C Leszek Rutkowski,Rafał Scherer,Jacek M. Zurada Conference proceedings 2023

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Unsupervised Pose Estimation by Means of an Innovative Vision Transformersformer architecture developed for CV is the Vision Transformer (ViT) [.]. ViT models have been used to solve numerous tasks in the CV area. One interesting task is the pose estimation of a human subject. We present our modified ViT model, . (UNsupervised TRAnsformer for Pose Estimation), that can r

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Semantically Consistent Sim-to-Real Image Translation with Neural Networkse real ones to train Computer Vision methods. Autonomous driving research could largely benefit from this as its neural network-based perception systems need a large amount of labeled training data. However, the sim-to-real texture swapping is a demanding challenge because of the large gap between t

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A Streaming Approach to the Core Vector Machine Both algorithms have nice theoretical guarantees, but are not able to handle data streams, which have to be processed instance by instance. We propose a novel approach to handle stream classification problems via an adaption of the CVM, which is also able to handle multiclass classification problem

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Identifying Cannabis Use Risk Through Social Media Based on Deep Learning Methods process of classifying online posts to identify cannabis use problems and their associated risks as early as possible. We annotated 11,008 online posts, which we used to build robust classification models. We tested classical and deep learning classifiers. Different CNN- and RNN-based models proved

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