Results 191 to 200 of about 26,697 (249)

Bridge Points Guided Neural Motion Planning in Complex Environments with Narrow Passages. [PDF]

Sensors (Basel)
Dian S, Liu J, Xiang G, You X.
europepmc   +1 more source

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

Fully synthetic replication of complex real biological cell clusters using a novel cluster-based 'Rosetta-Routine' computational modelling process. [PDF]

PLoS Comput Biol
Mason B, Justham L, Whitby L, Whitby A, Scott S, Nti S, Petzing J.   +6 more
europepmc   +1 more source

IoTDI-ImbS: A Precise Identification Model and Algorithm for IoT Devices from Network Traffic. [PDF]

Sensors (Basel)
Qian J, Zhao S, Wang Z, Li Z.
europepmc   +1 more source

Wasserstein GAN-based estimation for conditional distribution function with current status data. [PDF]

Lifetime Data Anal
Su W, Liu C, Yin G, Huang J.
europepmc   +1 more source

PFTuner: An Efficient and Effective Multi-Objective Configuration Tuning Framework Adaptive to Different Software Systems. [PDF]

Sensors (Basel)
Feng J, He M, Jin L, Dou H.
europepmc   +1 more source

Light-Induced Entropy for Secure Vision. [PDF]

Adv Mater
Seo J, Kang S, Kim C, Park T, Yoo Y, Kim YK, Shin W, Jang BC, Kim YJ, Yoo H.   +9 more
europepmc   +1 more source

Efficient industrial point cloud anomaly detection via spatial context aggregation and selective anomalous feature generation. [PDF]

Sci Rep
Hoang DC, Tan PX, Nguyen AN, Le M, Duong THA, Huynh TM, Nguyen DM, Cao MD, Ngo DH, Vu MQ, Nguyen TU, Phan KT, Do MQ, Dinh XT, Duong VH, Nguyen VT.   +15 more
europepmc   +1 more source

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True Random Number Generators

2014
Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulation, industrial testing and labeling, hazard games, gambling, etc. Our assumption has been that random numbers cannot be computed ; because digital computers operate deterministically, they cannot produce random umbrs.
Mario Stipčević, Çetin Kaya Koç
openaire   +2 more sources