AIMC Topic: Semantics

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Semantic code clone detection using hybrid intermediate representations and BiLSTM networks.

PloS one
Semantic code clone detection plays an essential role in software maintenance and quality assurance, as it helps uncover fragments of code that express the same logic even when their syntax has been altered or deliberately obfuscated. In this study, ...

Mitigating semantic label divergence in federated learning: Obfuscated encoding and alert filtering for security monitoring.

PloS one
Federated learning (FL) is emerging as a key approach for collaborative machine learning (ML) in distributed information systems where direct data sharing is infeasible due to policy constraints. In security operations center (SOC) settings, we study...

RadCLARE: an automated clinical language engine for detecting semantic errors in radiology reports.

European radiology experimental
BACKGROUND: Errors in radiology reports can result in inappropriate/harmful decisions. We investigated whether large language models can reduce the error rate.

H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics.

International journal of health geographics
BACKGROUND: Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are t...

A boundary enhanced multi-task neural attention approach for Chinese named entity recognition.

Scientific reports
Named Entity Recognition (NER) stands as a fundamental task in Chinese information processing. However, it encounters unique difficulties due to the lack of explicit word boundaries in the Chinese language. This study proposes framing Chinese NER as ...

English-focused CL-HAMC with contrastive learning and hierarchical attention for multiple-choice reading comprehension.

Scientific reports
Multiple-choice questions constitute a critical format for assessing language application proficiency in standardized English tests, such as BEC and TOEIC. Developing explanatory content for such materials traditionally relies heavily on manual labor...

Zero-shot image classification based on class representation learning and attribute embedding learning.

PloS one
Zero-shot learning (ZSL) aims to classify unseen classes by leveraging semantic information from seen classes, addressing the challenge of limited labeled data. In recent years, ZSL methods have focused on extracting attribute-level features from ima...

Prediction of uterine cavity conception environment using two-dimensional transvaginal ultrasound imaging semantic feature-based machine learning: a case-control study.

BMC pregnancy and childbirth
BACKGROUND: Independently investigating the association between pregnancy outcomes and the uterine cavity conception environment (UCCE) is challenging. Therefore, this study aimed to employ a range of machine learning algorithms to systematically ana...

A visual question answering method based on task decomposition.

PloS one
Visual question answering (VQA) as an interdisciplinary task of computer vision and natural language processing, estimating the model's visual reasoning ability, which requires the integration of image information extraction technology and natural la...

Hierarchical attention mechanism combined with deep neural networks for accurate semantic segmentation of dental structures in panoramic radiographs.

Scientific reports
Computer vision, a rapidly advancing branch of artificial intelligence (AI), has gained significant attention in medical and dental applications. Semantic segmentation, a key technique within computer vision, enables the precise identification and de...