Neural networks : the official journal of the International Neural Network Society
40106931
Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these m...
Deep learning has been successfully applied to histopathology image classification tasks. However, the performance of deep models is data-driven, and the acquisition and annotation of pathological image samples are difficult, which limit the model's ...
Neural networks : the official journal of the International Neural Network Society
40106927
Effective visual representation is crucial for image captioning task. Among the existing methods, the grid-based visual encoding methods take fragmented features extracted from the entire image as input, lacking the fine-grained semantic information ...
BMC medical informatics and decision making
40102785
BACKGROUND: In this era of active online communication, patients increasingly share their healthcare experiences, concerns, and needs across digital platforms. Leveraging these vast repositories of real-world information, Digital Listening enables th...
Neural networks : the official journal of the International Neural Network Society
40101559
Convolutional neural networks (CNNs) are highly regarded for their ability to extract semantic information from visual inputs. However, this capability often leads to the inadvertent loss of important visual details. In this paper, we introduce an Ad...
Neural networks : the official journal of the International Neural Network Society
40101558
Few-shot Knowledge Graph Completion (FKGC), an emerging technology capable of inferring new triples using only a few reference relation triples, has gained significant attention in recent years. However, existing FKGC methods primarily focus on struc...
Neural networks : the official journal of the International Neural Network Society
40096765
Recently, cross-scene hyperspectral image classification(HSIC) via domain adaptation is drawing increasing attention. However, most existing methods either directly align the source domain and target domain without fully mining of SD information, or ...
Effective representation of medical concepts is crucial for secondary analyses of electronic health records. Neural language models have shown promise in automatically deriving medical concept representations from clinical data. However, the comparat...
Neural networks : the official journal of the International Neural Network Society
40086133
Human-object interaction (HOI) detection aims to locate human-object pairs and identify their interaction categories in images. Most existing methods primarily focus on supervised learning, which relies on extensive manual HOI annotations. Such heavy...
International journal of molecular sciences
40076956
The aim of this study is to conduct a comparative assessment of the effectiveness of neural network models-U-Net, DeepLabV3+, SegNet and Mask R-CNN-for the semantic segmentation of micrographs of human mesenchymal stem cells (MSCs). A dataset of 320 ...