Results 191 to 200 of about 18,237 (266)

Upsampling DINOv2 Features for Unsupervised Vision Tasks and Weakly Supervised Materials Segmentation

open access: yesAdvanced Intelligent Systems, EarlyView.
Feature from recent image foundation models (DINOv2) are useful for vision tasks (segmentation, object localization) with little or no human input. Once upsampled, they can be used for weakly supervised micrograph segmentation, achieving strong results when compared to classical features (blurs, edge detection) across a range of material systems.
Ronan Docherty   +2 more
wiley   +1 more source

Terrestrial Cyborg Insects for Real‐Life Applications

open access: yesAdvanced Intelligent Systems, EarlyView.
This article reviews the development of terrestrial cyborg insects from their emergence in 1997 to mid‐2025, examining three key aspects: locomotion control methods, associated challenges with proposed solutions, and practical applications. Framing these biohybrid systems as insect‐scale mobile robots, the review provides foundational insights for new ...
Hai Nhan Le   +10 more
wiley   +1 more source

Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles

open access: yesAdvanced Intelligent Systems, EarlyView.
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin   +4 more
wiley   +1 more source

TacEva: A Performance Evaluation Framework for Vision‐Based Tactile Sensors

open access: yesAdvanced Intelligent Systems, EarlyView.
This work introduces TacEva, a unified framework for evaluating vision‐based tactile sensors. It standardizes intrinsic, performance, and robustness metrics through shared experimental procedures and links them to task‐level requirements in robotic manipulation.
Qingzheng Cong   +5 more
wiley   +1 more source

A Neural Network‐Based Self‐Sensing Embedded Position Control System for Shape Memory Alloy Wire Actuators

open access: yesAdvanced Intelligent Systems, EarlyView.
Shape memory alloy wires exhibit thermally induced phase changes that generate actuation strain and resistance variations enabling self‐sensing. However, hysteretic electromechanical behavior complicates accurate state estimation. This paper presents an artificial in‐based self‐sensing method to reconstruct SMA actuator position in real time, achieving
Krunal Koshiya   +2 more
wiley   +1 more source

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