Neural networks : the official journal of the International Neural Network Society
Apr 19, 2025
Introducing learnable prompts into CLIP and fine-tuning them have demonstrated excellent performance across many downstream tasks. However, existing methods have insufficient interaction between modalities and neglect the importance of hierarchical c...
Predicting molecular and quantum material properties, especially the band gap, is crucial for accelerating discoveries in drug design and material science. Although graph neural networks and probabilistic encoders are well established in molecular da...
BACKGROUND: Mass Spectrometry Imaging (MSI) is a label-free imaging technique used in spatial metabolomics to explore the distribution of various metabolites within biological tissues. Spatial segmentation plays a crucial role in the biochemical inte...
Since the outbreak of the COVID-19 pandemic in 2019, medical imaging has emerged as a primary modality for diagnosing COVID-19 pneumonia. In clinical settings, the segmentation of lung infections from computed tomography images enables rapid and accu...
Denial of Wallet (DoW) attacks are a cyber threat designed to utilize and deplete an organization's financial resources by generating excessive prices or charges in their cloud computing (CC) and serverless computing platforms. These threats are prim...
Increasing the number of organ donations after circulatory death (DCD) has been identified as one of the most important ways of addressing the ongoing organ shortage. While recent technological advances in organ transplantation have increased their s...
Food research international (Ottawa, Ont.)
Apr 18, 2025
A rapid and chemical-free method based on hyperspectral imaging (HSI) integrated with artificial intelligence (AI) for monitoring dried shrimp quality was developed. Dried shrimp was packaged in a polypropylene bag and chronologically monitored for c...
Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large training datasets while making limited use of prior geometric knowledge. Th...
Capturing rich multi-scale features is essential to address complex variations in medical image segmentation. Multiple hybrid networks have been developed to integrate the complementary benefits of convolutional neural networks (CNN) and Transformers...
International journal of surgery (London, England)
Apr 18, 2025
BACKGROUND: Recent years have witnessed a proliferation of studies aimed at developing clinical models capable of predicting lymph node metastasis (LNM) in early gastric cancer (EGC), yet tools for prediction grounded in the Lauren classification rem...
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