Results 201 to 210 of about 1,051,485 (290)

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

Neuroimaging PheWAS and molecular phenotyping implicate PSMC3 in Alzheimer's disease. [PDF]

Alzheimers Dement
Bledsoe X, Wang TC, Wu Y, Archer D, Chen HH, Naj AC, Bush WS, Hohman TJ, Dumitrescu L, Below JE, Gamazon ER.   +10 more
europepmc   +1 more source

NIRGB‐GS: Near‐Infrared Assisted Low‐Light Scene Reconstruction and Enhancement via Gaussian Splatting

Advanced Intelligent Systems, EarlyView.
This article proposes NIRGB‐GS, a multimodal 3DGS variant that enables reliable 3D reconstruction and normal‐light novel‐view synthesis for extremely low‐light scenes by fusing paired near‐infrared and noisy RGB captures. High‐SNR near‐infrared modality and modality‐specific appearance encoding together resolve the issues of unstable pose/geometry ...
Chengyun Yang, Yi Zhang, Yu Lei, Qiaofeng Li   +3 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
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, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Quantum-like Cognition and Decision-Making: Interpretation of Phases in Quantum-like Superposition. [PDF]

Entropy (Basel)
Khrennikov A.
europepmc   +1 more source

Collaborative Visual Localization for Modular Self‐Reconfigurable Robots

Advanced Intelligent Systems, EarlyView.
Relative localization in modular self‐reconfigurable robots is challenged by hardware limitations, constrained fields of view, and sensor faults. This paper, based on the SnailBot platform, presents a vision‐based collaborative localization method that combines ArUco markers with learning‐based algorithms to enable robust pose estimation from ...
Guanqi Liang, Rong Ou, Peiqi Wang, Xianghong Wang, Tin Lun Lam   +4 more
wiley   +1 more source

Multiscale metabolic covariance networks uncover stage-specific biomarker signatures across the Alzheimer's disease continuum. [PDF]

Alzheimers Dement
Chong Chie JAK, Persohn SA, Pandey RS, Simcox OR, Carter G, Salama P, Territo PR, Alzheimer's Disease Neuroimaging Initiative.   +7 more
europepmc   +1 more source

Generalized Task‐Driven Design of Soft Robots via Reduced‐Order Finite Element Method‐Based Surrogate Modeling

Advanced Intelligent Systems, EarlyView.
A unified, reusable modeling pipeline enables task‐driven design of soft robots across actuator families and task scenarios. High‐fidelity simulations are compressed into compact pseudo‐rigid‐body joint surrogates, while a design‐conditioned meta‐model generates new surrogates from geometry parameters without rerunning finite element method.
Yao Yao, David Howard, Perla Maiolino
wiley   +1 more source

Multivariate Regression With Dependence Structures: Evaluating Associations Between Plasma Metabolomics and Alcohol Intake in Older Adults. [PDF]

Stat Med
Yang Y, Chen C, Lee H, Wang M, Zhang Y, Chen S.   +5 more
europepmc   +1 more source

Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning

Advanced 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, Zichao Wang, Zhiwei He, Qingquan Wei, Yong Zuo, Linzhen Nie, Zhishuai Yin   +6 more
wiley   +1 more source