Results 301 to 310 of about 13,525,492 (371)

Edge Information‐Augmented Auxiliary Diagnosis Method for Cervical Cancer in Medical Decision‐Making Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
To address the problems of insufficient utilization of multiscale features and inefficient feature sharing between tasks in the model, this study proposes an edge‐enhanced intelligent cervical cancer screening method that achieves feature reuse and improves efficiency by jointly optimizing nucleolus segmentation and lesion classification.
Li Wen   +4 more
wiley   +1 more source

Phase‐Change Alloys Enable Localized Reversible Stiffening and Actuation in Steerable Eversion Tip‐Growing Robots

open access: yesAdvanced Intelligent Systems, EarlyView.
This work presents a tip‐growing eversion robot that uses phase‐changing alloys for reversible stiffening and localized actuation, achieving 43× stiffness modulation, 15× force amplification, and segmental steering. The system enables precise navigation and force delivery in constrained, tortuous pathways.
Shamsa Al Harthy   +4 more
wiley   +1 more source

A Female‐Locust‐Inspired Hybrid Soft‐Stiff Robotic Digger: Mimetics and Implications for Digging Efficiency

open access: yesAdvanced Intelligent Systems, EarlyView.
Female desert locusts dig underground to lay their eggs. They displace soil, rather than removing it, to create a tunnel. We analyze burrowing dynamics and 3D kinematics and design a locust‐inspired hybrid soft–stiff robot that reproduces this mechanism. The results show the natural strategy minimizes energy, whereas alternative patterns raise costs up
Shai Sonnenreich   +2 more
wiley   +1 more source

Collaborative Multiagent Closed‐Loop Motion Planning for Multimanipulator Systems

open access: yesAdvanced Intelligent Systems, EarlyView.
This work presents a hierarchical multi‐manipulator planner, emphasizing highly overlapping space. The proposed method leverages an enhanced Dynamic Movement Primitive based planner along with an improvised Multi‐Agent Reinforcement Learning approach to ensure regulatory and mediatory control while ensuring low‐level autonomy. Experiments across varied
Tian Xu, Siddharth Singh, Qing Chang
wiley   +1 more source

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