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Abstract Deep learning-based image semantic segmentation techniques have made great strides in recent years. However, they still need large amounts of finely annotated image data, and generalizing the model from known cl...

This paper offers a systematic and interdisciplinary analysis of contemporary work on memory externalization, with a particular focus on how technological systems are integrated into human mnemonic practices. Drawing on ...

Non-monotonic base-extension semantics (nB-eS), a kind of non-monotonic proof-theoretic semantics (nPTS), is known to validate classical logic when its meta-logic is classical. Schroeder-Heister has remarked that classic...

Precision agriculture plays a crucial role in sustainable food production and resource-efficient land management. A key component of precision agriculture is the semantic segmentation of crops and weeds that enables auto...

Button batteries, which serve as essential power sources in consumer electronics, are susceptible to various manufacturing defects that pose potential safety risks. This study proposes LMG-YOLO, an enhanced algorithm bas...

Small businesses often handle customer questions through manual replies via chat applications or phone calls, causing repetitive work, delayed responses, and inconsistent information delivery. This study proposes a web-b...

Abstract Cross-lingual information retrieval limits global exchange of data because of the high diversity in the methods to classify, document and encode medical procedures. Traditional keyword-based or single-language s...

The rapid growth of e-commerce has led to product overload, which has resulted in personalized product discovery becoming a crucial problem for consumers. Classic recommender systems (RS), which rely heavily on content-b...

The classification of Chinese phrase structures has traditionally been based on formal configuration, especially categories such as subject-predicate, verb-object, and modifier-head constructions. Although this approach ...

Weakly supervised semantic segmentation (WSSS), particularly using image-level labels, has emerged as a pivotal solution to alleviate the burden of costly and labor-intensive pixel-level annotations typically required fo...

The article investigates the phenomenon of hate speech in the criminogenic discourse of social networks, where discriminatory and aggressive communicative practices are employed as instruments of informational and psycho...

Abstract Background Reliable identification of protein‑protein interactions (PPIs) is crucial for deciphering cellular functional networks. Current research models still face limitations in aligning heterogeneous featu...

Introduction and aims: Automated dental report generation faces significant challenges in multimodal fusion, often resulting in suboptimal semantic quality and risks of hallucination, where AI generates clinically unsupp...

With the rise of generative AI, a new generation of intelligent phishing has emerged, where attackers leverage Large Language Models (LLMs) to craft websites with high semantic plausibility, posing critical challenges to...

Abstract This study introduces an intelligent, large language model (LLM)–driven feedback system designed to assess and enhance students’ programming tasks through semantic comparison and pedagogically contextualized...

Abstract Substation drawings are high-density technical artifacts that serve as the authoritative data source across the entire power-infrastructure lifecycle. Manual auditing of these drawings is labor-intensive, error-...

The field of remote sensing change detection (RSCD) has witnessed remarkable progress. Most existing RSCD methods currently follow the encoder-feature interaction-decoder architecture. However, these methods often treat ...

Understanding how semantic information flow reorganizes market topology remains an open challenge in financial network analysis. Prior work typically emphasizes price correlations or sentiment polarity, but rarely quanti...

INTRODUCTION. The study is devoted to the description of a as one of the effective modern methods of word research, its identification, perception in the linguistic consciousness of a native speaker and reflection of the...

IntroductionThe escalating frequency of infectious disease outbreaks underscores the urgent need for reliable forecasting systems to support timely public health interventions. Existing approaches—ranging from statisti...

Communication is moving from being data-centric to being experience-centric and perception-aware with the advent of 6G wireless networks. Immersive applications such as digital twins, holographic telepresence, extended r...

Novel innovations in large language models (LLMs) have demonstrated their ability to generate and analyze literary texts. As a result of intricate semantic layers, metaphors, polyphony, and nonlinear narrative structures...

Dialogue systems frequently misinterpret user input containing vague, hedged, or perception-based expressions such as “somewhat warm” or “not bright”. Traditional sentence similarity measures ...

Column type annotation (CTA) is a critical task in semantic table interpretation (STI), where meaningful semantic labels are automatically assigned to table columns. This process enriches tabular data with essential sema...