Semantic information - Open Access .click

Results 111 to 120 of about 167,283 (265)

Multi-Modality Image Fusion and Object Detection Based on Semantic Information. [PDF]

Entropy (Basel), 2023
Liu Y, Zhou X, Zhong W.
europepmc +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu +3 more
wiley +1 more source

Fusion Network for Aspect-Level Sentiment Classification Based on Graph Neural Networks—Enhanced Syntactics and Semantics

Applied Sciences
Aspect-level sentiment classification (ALSC) struggles with correctly trapping the aspects and corresponding sentiment polarity of a statement. Recently, several works have combined the syntactic structure and semantic information of sentences for more ...
Miaomiao Li, Yuxia Lei, Weiqiang Zhou
doaj +1 more source

A Novel Strategy for Extracting Richer Semantic Information Based on Fault Detection in Power Transmission Lines. [PDF]

Entropy (Basel), 2023
Yan S, Li J, Wang J, Liu G, Ai A, Liu R.
europepmc +1 more source

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source

On the (Apparently) Paradoxical Role of Noise in the Recognition of Signal Character of Minor Principal Components

Stats
The usual method of separating signal and noise principal components on the sole basis of their eigenvalues has evident drawbacks when semantically relevant information ‘hides’ in minor components, explaining a very small part of the total variance. This
Alessandro Giuliani, Alessandro Vici
doaj +1 more source

Reviewing Evolution of Learning Functions and Semantic Information Measures for Understanding Deep Learning. [PDF]

Entropy (Basel), 2023
Lu C.
europepmc +1 more source

An Integrated NLP‐ML Framework for Property Prediction and Design of Steels

Advanced Science, EarlyView.
This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source

stMixer for Scalable Mosaic Integration and Label Transfer in Spatial Histology and Multi‐Omics

Advanced Science, EarlyView.
stMixer is an unsupervised framework for scalable integration and label transfer across spatial histology and multi‐slide multi‐omics data with incomplete modality overlap. It combines self‐looped cross‐attention, multimodal metric learning, and graph‐guided cluster voting to align heterogeneous sections, correct batch effects, and propagate ...
Qixing Yang, Yan Wang, Luonan Chen, Chunman Zuo +3 more
wiley +1 more source

Multi-step wind power prediction based on patch-wise attention mechanism

电力工程技术
Effective feature representation is crucial for machine learning-based wind power prediction. Existing studies typically employ point-wise attention mechanisms to learn features at each time step of the wind power time series.
Bixing REN +4 more
doaj +1 more source