Results 51 to 60 of about 2,336,780 (253)
Blackboard Agents for Standard Arabic Language Tokenization and Parsing
The Processing of the Arabic language is a difficult mission comparing it with other languages. Because Sentences in Arabic language are complex, longer than the others in various languages, and have difficult structure with lattices.
Abdul Kareem Murhij Radhi
doaj
Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models
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
tutpresentTutorialPresentationInteractive Media ElementThis is a tutorial on Top-Down Parsing. It explains how it works and provides an activity at the end to demonstrate the steps involved in a given example.SW4150Software Tools and ...
core +1 more source
LLM‐Integrated Human–Robot Interaction System for Microrobots
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley +1 more source
Bottom-up/top-down image parsing by attribute graph grammar [PDF]
In this paper, we present an attribute graph grammar for image parsing on scenes with man-made objects, such as buildings, hallways, kitchens, and living moms. We choose one class of primitives - 3D planar rectangles projected on images and six graph grammar production rules.
Feng Han 0001, Song Chun Zhu
openaire +2 more sources
Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences
This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
Efficient Top-Down BTG Parsing for Machine Translation Preordering [PDF]
We present an efficient incremental topdown parsing method for preordering based on Bracketing Transduction Grammar (BTG). The BTG-based preordering framework (Neubig et al., 2012) can be applied to any language using only parallel text, but has the problem of computational efficiency.
openaire +1 more source
Protein Identication from Top-Down Mass Spectra, a Fast Filtering Algorithm [PDF]
La spettrometria di massa top-down e' un campo abbastanza nuovo della proteomica che offre ottime prospettive. Le risorse informatiche, pero', non sono ancora mature.
Mammana , Alessandro
core
Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram +4 more
wiley +1 more source

