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In this paper, we propose a novel hybrid transformer architecture for food cuisine detection and classification. The work carried out within this paper develops a combination of Vision Transformer ensemble architecture with hand-crafted features, thereby making a hybrid Vision Transformer food recognition system. Recently, Vision transformers have been introduced as an alternative means of classification to convolutional neural networks. It performs pattern detection and classification without convolutions and interprets an image as a sequence of patches. The combination of Vision Transformer ...

Objective: Parkinson's disease (PD) is a common neurological disorder with variable clinical manifestations and magnetic resonance imaging (MRI) findings. We propose a handcrafted image classification model that can accurately (i) classify different PD stages, (ii) detect comorbid dementia, and (iii) discriminate PD-related motor symptoms. Methods: Selected image datasets from three PD studies were used to develop the classification model. Our proposed novel automated system was developed in four phases: (i) texture features are extracted from the non-fixed size patches. In the feature ex...

This paper shows different Pummel classifications that can currently be found on the market. Subsequently, approaches to the automatization and standardization of the execution and especially the evaluation of the Pummel test are shown.