Due to the wide variety of medical images and the complexity of the human body structure, the characteristics of manual extraction of medical images are difficult, the adaptive ability is poor, and the classification effect needs to be improved.Aiming at the shortcomings of traditional medical image recognition methods, this paper proposes an adapt
Douglas R Pedersen, Jessica E Goetz, Gail L Kurriger, James A MartinDepartment of MAGNESIUM MALATE Orthopaedics and Rehabilitation, University of Iowa, Iowa City, IA, USAPurpose: This study addresses the species-specific and site-specific details of weight-bearing articular cartilage zone depths and chondrocyte distributions among humans and common
Proterosuchidae represents the oldest substantial diversification of Archosauromorpha and plays a key role in understanding the biotic recovery after the end-Permian mass extinction.Proterosuchidae was long treated as a wastebasket taxon, but recent revisions have Camera Strap reduced its taxonomic content to five valid species from the latest Perm
Graph neural ETi 250 Parts networks (GNNs) have shown great promise in few-shot learning, where they typically represent the entire feature of a sample as a node.However, this approach can overlook finer details within the sample, as GNNs usually measure the distance between nodes to determine overall differences, making them prone to background no