Results 61 to 70 of about 254,529 (285)

ParsBERT: Transformer-based Model for Persian Language Understanding

, 2020
The surge of pre-trained language models has begun a new era in the field of Natural Language Processing (NLP) by allowing us to build powerful language models.
Farahani, Marzieh, Farahani, Mehrdad, Gharachorloo, Mohammad, Manthouri, Mohammad   +3 more
core   +1 more source

PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science

Advanced Engineering Materials, EarlyView.
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley   +1 more source

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Chinese named entity identification using cascaded hidden Markov model

Tongxin xuebao, 2006
An approach for Chinese named entity identification using cascaded hidden Markov model,which aimed to incorporate person name,location name,organization name recognition into an integrated theoretical frame was presented.Simple named entity was ...
YU Hong-kui1, ZHANG Hua-ping1, LIU Qun1, LV Xue-qiang2, SHI Shui-cai2   +4 more
doaj   +2 more sources

Enhancing biomedical named entity recognition with parallel boundary detection and category classification

BMC Bioinformatics
Background Named entity recognition is a fundamental task in natural language processing. Recognizing entities in biomedical text, known as the BioNER, is particularly crucial for cutting-edge applications.
Yu Wang, Hanghang Tong, Ziye Zhu, Fengzhen Hou, Yun Li   +4 more
doaj   +1 more source

MLNet: a multi-level multimodal named entity recognition architecture

Frontiers in Neurorobotics, 2023
In the field of human–computer interaction, accurate identification of talking objects can help robots to accomplish subsequent tasks such as decision-making or recommendation; therefore, object determination is of great interest as a pre-requisite task.
Hanming Zhai, Xiaojun Lv, Zhiwen Hou, Xin Tong, Fanliang Bu   +4 more
doaj   +1 more source

On–Off Switchable Micromotors for Use in Steerable Microvehicles

Advanced Robotics Research, EarlyView.
Electrically controllable micromotors and microvehicles are developed by tuning the diffusion of the fuel. Self‐propelled micromotors using bubble propulsion show great promise for miniaturized devices with multiuse purposes such as cargo delivery and sensing. However, there is currently no method to electrically switch the micromotors on or off. Here,
Hugo Severinsson, Eswaran Murugasen, Jose G. Martinez, Edwin W. H. Jager   +3 more
wiley   +1 more source

Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries

BMC Bioinformatics, 2019
* Background Consisting of dictated free-text documents such as discharge summaries, medical narratives are widely used in medical natural language processing.
Yipei Wang, Xingyu Fan, Luoxin Chen, Eric I-Chao Chang, Sophia Ananiadou, Junichi Tsujii, Yan Xu   +6 more
doaj   +1 more source

Neurals Networks for Projecting Named Entities from English to Ewondo

, 2020
Named entity recognition is an important task in natural language processing. It is very well studied for rich language, but still under explored for low-resource languages. The main reason is that the existing techniques required a lot of annotated data
Lombo, Guy Stephane B. Fedim, Mbouopda, Michael Franklin, Yonta, Paulin Melatagia   +2 more
core  

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

Advanced 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, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source