Results 101 to 110 of about 528,999 (295)

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

open access: yesAdvanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

open access: yesAdvanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Information Extraction Using Distant Supervision and Semantic Similarities

open access: yesAdvances in Electrical and Computer Engineering, 2016
Information extraction is one of the main research tasks in natural language processing and text mining that extracts useful information from unstructured sentences. Information extraction techniques include named entity recognition, relation extraction,
PARK, Y., KANG, S., SEO, J.
doaj   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

open access: yesAdvanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki   +2 more
wiley   +1 more source

Machine‐Learning Decomposition Identifies a Big Two Structure in Human Personality with Distinct Neurocognitive Profiles

open access: yesAdvanced Science, EarlyView.
Using machine learning on a mega‐scale global dataset (n = 1,336,840) reveals a robust personality trait architecture beyond the Big Five. A Big Two model, broadly capturing social engagement and internal mentation, defines a geometric space that links personality to neurocognitive profiles.
Kaixiang Zhuang   +7 more
wiley   +1 more source

Specification of vertical semantic consistency rules of UML class diagram refinement using logical approach [PDF]

open access: yes, 2014
Unified Modelling Language (UML) is the most popular modelling language use for software design in software development industries with a class diagram being the most frequently use diagram.
Nuraini Abdulganiyyi, Nuraini
core  

Farnesyltransferase Deficiency in Cardiomyocytes Initiates Senescence and Contributes to Cardiac Fibrosis

open access: yesAdvanced Science, EarlyView.
Lipid overload suppresses SREBF2‐mediated FNTB expression, leading to defective Lamin A maturation and nuclear envelope instability. This nuclear catastrophe triggers a pro‐fibrotic senescence program in cardiomyocytes. Notably, restoring nuclear integrity via AAV9‐based gene therapy effectively attenuates cardiac remodeling, identifying the ...
Yuxiao Chen   +16 more
wiley   +1 more source

Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases

open access: yesBMC Medical Informatics and Decision Making, 2018
Background In the past few years, neural word embeddings have been widely used in text mining. However, the vector representations of word embeddings mostly act as a black box in downstream applications using them, thereby limiting their interpretability.
Zhiwei Chen   +3 more
doaj   +1 more source

A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge [PDF]

open access: yes, 2013
We present the architecture and the evaluation of a new system for recognizing textual entailment (RTE). In RTE we want to identify automatically the type of a logical relation between two input texts.
Coote, Ravi, Wotzlaw, Andreas
core  

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