Results 191 to 200 of about 238,312 (311)
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu +2 more
wiley +1 more source
A dual-consistency semi-supervised learning method for histopathology image segmentation. [PDF]
Xie M +6 more
europepmc +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Collaborative representation and confidence-driven semi-supervised learning for hyperspectral image classification. [PDF]
Chen Y, Lu H, Huang X.
europepmc +1 more source
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley +1 more source
Similarity-guided swarm of models: enhancing semi-supervised learning in computational pathology. [PDF]
Weng Z +9 more
europepmc +1 more source
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Semi-supervised active learning in graphical domains
In a traditional machine learning task, the goal is training a classifier using only labeled data (data feature/label pairs) in order to be able to generalize on completely new data to be labeled by the classifier. Unluckily in many cases it is difficult,
PUCCI, AUGUSTO +2 more
core
Towards Advanced Intelligent and Perceptive Soft Grippers
Implementing soft yet strong and intelligent soft grippers request innovative and creative solutions in designing soft bodies and seamlessly integrating actuated systems with hierarchical sensing. This review systematically analyses soft grippers with a deep understanding of core components, from fundamental design principles to actuation and sensing ...
Haneul Kim +4 more
wiley +1 more source
Source-Free Domain-Adaptive Semi-Supervised Learning for Object Detection in CCTV Images. [PDF]
Shin H, Kim GY.
europepmc +1 more source

