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Semantics

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Noise-robust consistency regularization for semi-supervised semantic segmentation.

Neural networks : the official journal of the International Neural Network Society
The essential of semi-supervised semantic segmentation (SSSS) is to learn more helpful information from unlabeled data, which can be achieved by assigning adequate quality pseudo-labels or managing noisy pseudo-labels during training. However, most r...

Semantically-Enhanced Feature Extraction with CLIP and Transformer Networks for Driver Fatigue Detection.

Sensors (Basel, Switzerland)
Drowsy driving is a leading cause of commercial vehicle traffic crashes. The trend is to train fatigue detection models using deep neural networks on driver video data, but challenges remain in coarse and incomplete high-level feature extraction and ...

Relation Extraction in Biomedical Texts: A Cross-Sentence Approach.

IEEE/ACM transactions on computational biology and bioinformatics
Relation extraction, a crucial task in understanding the intricate relationships between entities in biomedical domains, has predominantly focused on binary relations within single sentences. However, in practical biomedical scenarios, relationships ...

Coherence and comprehensibility: Large language models predict lay understanding of health-related content.

Journal of biomedical informatics
Health literacy is a prerequisite to informed health-related decision making. To facilitate understanding of information, text should be presented at an appropriate reading level for the reader. Cognitive studies suggest that the coherence of a text ...

Dual-tower model with semantic perception and timespan-coupled hypergraph for next-basket recommendation.

Neural networks : the official journal of the International Neural Network Society
Next basket recommendation (NBR) is an essential task within the realm of recommendation systems and is dedicated to the anticipation of user preferences in the next moment based on the analysis of users' historical sequences of engaged baskets. Curr...

geodl: An R package for geospatial deep learning semantic segmentation using torch and terra.

PloS one
Convolutional neural network (CNN)-based deep learning (DL) methods have transformed the analysis of geospatial, Earth observation, and geophysical data due to their ability to model spatial context information at multiple scales. Such methods are es...

Nonnegative matrix factorization with Wasserstein metric-based regularization for enhanced text embedding.

PloS one
Text embedding plays a crucial role in natural language processing (NLP). Among various approaches, nonnegative matrix factorization (NMF) is an effective method for this purpose. However, the standard NMF approach, fundamentally based on the bag-of-...

CPRS: a clinical protocol recommendation system based on LLMs.

International journal of medical informatics
BACKGROUND: As fundamental documents in clinical trials, clinical trial protocols are intended to ensure that trials are conducted according to the objectives set by researchers. The advent of large models with superior semantic performance compared ...

Heterogeneous Graph Embedding with Dual Edge Differentiation.

Neural networks : the official journal of the International Neural Network Society
Recently, heterogeneous graphs have attracted widespread attention as a powerful and practical superclass of traditional homogeneous graphs, which reflect the multi-type node entities and edge relations in the real world. Most existing methods adopt ...

Semantic Mask Reconstruction and Category Semantic Learning for few-shot image generation.

Neural networks : the official journal of the International Neural Network Society
Few-shot image generation aims at generating novel images for the unseen category when given K images from the same category. Despite significant advancements in existing few-shot image generation methods, great challenges remain regarding the qualit...