Results 231 to 240 of about 9,063,036 (352)

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

open access: yesAdvanced Intelligent Systems, EarlyView.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin   +4 more
wiley   +1 more source

MTCA‐Net: Multi‐Task Cascade Analysis Network for Real‐Time Sperm Quality Analysis

open access: yesAdvanced Intelligent Systems, EarlyView.
This article proposes MTCA‐Net, a multi‐task cascaded analysis network for real‐time sperm quality assessment in intracytoplasmic sperm injection. The framework integrates detection, tracking, and segmentation modules to jointly analyze sperm morphology and motility.
Jiajin Li   +10 more
wiley   +1 more source

Gate‐Align‐SED: Semi‐Supervised Sound Event Detection via Adaptive Feature Gating and Cross‐Task Alignment in Situation Awareness

open access: yesAdvanced Intelligent Systems, EarlyView.
Overview of the proposed Gate‐Align‐SED, including two stages of training: (1) Mean‐Teacher SSL Training; and (2) Enhancer Model Training. In complex real‐world environments such as disaster monitoring, effective sound event detection (SED) is often hindered by the presence of noise and limited labeled data.
Jieli Chen   +4 more
wiley   +1 more source

Concentric Rheostat Decoupled 3D Force‐Sensing Module for Smart Table Tennis Training

open access: yesAdvanced Intelligent Systems, EarlyView.
A 3D‐printed sensor array intrinsically decouples normal and shear forces through a unique concentric structural design. By integrating piezoresistive, sliding area‐varying capacitive, and concentric rheostat mechanisms, the 12‐sensor module achieves high‐resolution 3D force mapping without complex algorithms.
Zhe Liu   +7 more
wiley   +1 more source

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

open access: yesAdvanced Intelligent Systems, EarlyView.
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang   +6 more
wiley   +1 more source

Home - About - Disclaimer - Privacy