Results 161 to 170 of about 3,454,792 (299)
From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures
This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
wiley +1 more source
Reasoning in machine vision by learning fast and slow thinking. [PDF]
Saeed SU +6 more
europepmc +1 more source
Machine Vision and Human Vision
openaire +2 more sources
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 +3 more
wiley +1 more source
Development of a Machine Vision System for Liquid Handling using Deep Learning techniques
reservedLo scopo di questa tesi è presentare lo sviluppo di una componente di un sistema di machine vision, progettato per una strumentazione da laboratorio realizzata da M31 Srl e finalizzata alla manipolazione e all'analisi di campioni biologici.
D'OVIDIO, GIACOMO
core
Systematic image perturbations reveal persistent gaps between human and machine vision. [PDF]
Kato M, He BJ.
europepmc +1 more source
Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings +6 more
wiley +1 more source
Weld Width Measurement and Defect Detection Method for Desiccant Cartridges Based on Machine Vision. [PDF]
Wang Q +6 more
europepmc +1 more source
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source

