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Semantics

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A simple clustering approach to map the human brain's cortical semantic network organization during task.

NeuroImage
Constructing task-state large-scale brain networks can enhance our understanding of the organization of brain functions during cognitive tasks. The primary goal of brain network partitioning is to cluster functionally homogeneous brain regions. Howev...

A prompt tuning method based on relation graphs for few-shot relation extraction.

Neural networks : the official journal of the International Neural Network Society
Prompt-tuning has recently proven effective in addressing few-shot tasks. However, task resources remain severely limited in the specific domain of few-shot relation extraction. Despite its successes, prompt-tuning faces challenges distinguishing bet...

An Automated Approach for Domain-Specific Knowledge Graph Generation─Graph Measures and Characterization.

Journal of chemical information and modeling
In 2020, nearly 3 million scientific and engineering papers were published worldwide (White, K. Publications Output: U.S. Trends And International Comparisons). The vastness of the literature that already exists, the increasing rate of appearance of ...

Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer.

Scientific reports
Heart Rate Variability (HRV) serves as a vital marker of stress levels, with lower HRV indicating higher stress. It measures the variation in the time between heartbeats and offers insights into health. Artificial intelligence (AI) research aims to u...

Span-aware pre-trained network with deep information bottleneck for scientific entity relation extraction.

Neural networks : the official journal of the International Neural Network Society
Scientific entity relation extraction intends to promote the performance of each subtask through exploring the contextual representations with rich scientific semantics. However, most of existing models encounter the dilemma of scientific semantic di...

Break Adhesion: Triple adaptive-parsing for weakly supervised instance segmentation.

Neural networks : the official journal of the International Neural Network Society
Weakly supervised instance segmentation (WSIS) aims to identify individual instances from weakly supervised semantic segmentation precisely. Existing WSIS techniques primarily employ a unified, fixed threshold to identify all peaks in semantic maps. ...

A text-speech multimodal Chinese named entity recognition model for crop diseases and pests.

Scientific reports
Named Entity Recognition for crop diseases and pests (NER-CDP) is significant in agricultural information extraction and offers vital data support for subsequent knowledge services and retrieval. However, existing NER-CDP methods rely heavily on plai...

SH: Long-tailed classification via spatial constraint sampling, scalable network, and hybrid task.

Neural networks : the official journal of the International Neural Network Society
Long-tailed classification is a significant yet challenging vision task that aims to making the clearest decision boundaries via integrating semantic consistency and texture characteristics. Unlike prior methods, we design spatial constraint sampling...

A robotics-inspired scanpath model reveals the importance of uncertainty and semantic object cues for gaze guidance in dynamic scenes.

Journal of vision
The objects we perceive guide our eye movements when observing real-world dynamic scenes. Yet, gaze shifts and selective attention are critical for perceiving details and refining object boundaries. Object segmentation and gaze behavior are, however,...

Composition as Nonlinear Combination in Semantic Space: A Computational Characterization of Compound Processing.

Cognitive science
Most Chinese words are compounds formed through the combination of meaningful characters. Yet, due to compositional complexity, it is poorly understood how this combinatorial process affects the access to the whole-word meaning. In the present study,...