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Titlebook: Computer Vision Systems; 14th International C Henrik I. Christensen,Peter Corke,Markus Vincze Conference proceedings 2023 The Editor(s) (if

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Incidence, Prevalence, and Classificationinflammation, endocardium, and blood vessels. The study compares the experimental results of multiple methods evaluated using real data from medical experts. This study lays the groundwork for future research and demonstrates the potential of deep learning applied to the prediction of transplant rejection.
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https://doi.org/10.1007/978-3-642-37747-1ural network is trained, inference can be performed from the outer shape measured with cheap devices such as laser profilers. We demonstrate the effectiveness of our approach on fir and spruce tree species and perform ablation on the recurrence to demonstrate its importance.
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Slovo: Russian Sign Language Dataset data collection to video annotation, with the following demo application. Several neural networks are trained and evaluated on the Slovo to demonstrate its teaching ability. Proposed data and pre-trained models are publicly available.(.).(.).
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DeepLabV3+ Ensemble for Diagnosis of Cardiac Transplant Rejectioninflammation, endocardium, and blood vessels. The study compares the experimental results of multiple methods evaluated using real data from medical experts. This study lays the groundwork for future research and demonstrates the potential of deep learning applied to the prediction of transplant rejection.
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Tracking and Identification of Ice Hockey Playerst a comprehensive framework for player identification and tracking in ice hockey games, utilising deep neural networks trained on actual gameplay data. Player detection, identification, and tracking are the three main components of our architecture. The player detection component detects individuals
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Dedicated Encoding-Streams Based Spatio-Temporal Framework for Dynamic Person-Independent Facial Expes. The important attention given to the FER application is translated by the various architectures and datasets proposed to develop efficient automatic FER frameworks. This paper proposes a new, yet efficient appearance-based deep framework for dynamic FER referred to as Dedicated Encoding-streams
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Hands, Objects, Action! Egocentric 2D Hand-Based Action Recognitionf Daily Living (ADLs) without any conscious effort on the part of the user. This study explores the feasibility of using 2D hand and object pose information for egocentric action recognition. While current literature focuses on 3D hand pose information, our work shows that using 2D skeleton data is
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