Results 171 to 180 of about 9,519 (266)

Human‐in‐the‐Loop Object Segmentation for 3D Gaussian Splatting via Finger‐based VR Interface

Advanced Intelligent Systems, EarlyView.
This study introduces a human‐in‐the‐loop segmentation framework for 3D Gaussian Splatting that integrates real‐time optimization with intuitive VR‐based finger prompting. Compared with existing automatic, learning‐based methods, it achieves significantly higher accuracy and reduced segmentation time.
Yongseok Lee, Hyunreal Park, Hyunsu Kim, Harim Ji, Dongho Yee, Dongjun Lee   +5 more
wiley   +1 more source

Two-staged CT-based radiomics model in characterising early-stage ovarian carcinoma and benign ovarian masses. [PDF]

J Ovarian Res
Zhang J, Singh R, Wong EMF, Han L, Ho G, Chiu WHK, Cho IMK, Ip PPC, Lee EYP.   +8 more
europepmc   +1 more source

The Asymptotic Behavior of Bayes' Estimators

The Annals of Mathematical Statistics, 1970
openaire   +3 more sources

Lidar‐Based Object Tracking of Traffic Participants with Sensor Nodes in Existing Urban Infrastructure

Advanced Intelligent Systems, EarlyView.
This paper presents a lidar‐based sensor node design and a rule‐based state observer for edge‐based traffic participant tracking. Unlike other state‐of‐the‐art methods, this state observer enables real‐time, CPU‐only edge processing without relying on machine learning approaches.
Simon Schäfer, Bassam Alrifaee, Ehsan Hashemi   +2 more
wiley   +1 more source

TAN-FGBMLE: Tree-Augmented Naive Bayes Structure Learning Based on Fast Generative Bootstrap Maximum Likelihood Estimation for Continuous-Variable Classification. [PDF]

Entropy (Basel)
Wei C, Zhang T, Li C, Wang P, Ye Z.
europepmc   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Approximating evidence via bounded harmonic means. [PDF]

Stat Comput
Naderi D, Robert CP, Kamary K, Wraith D.
europepmc   +1 more source

Profiling Co‐Occurrent Morphological Phenotypes and Their Degree of Expression Severity in Vacuolated Cells by Holo‐Tomographic Flow Cytometry and Fractal Analysis

Advanced Intelligent Systems, EarlyView.
HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino, Giusy Giugliano, Daniele Pirone, Fabrizio Licitra, Fulvia Vitale, Pasquale Memmolo, Lisa Miccio, Massimo D’Agostino, Pietro Ferraro, Vittorio Bianco   +9 more
wiley   +1 more source

A Novel Version of the Arcsine-Rayleigh Distribution with Entropy Measures, Statistical Inference, and Applications. [PDF]

Entropy (Basel)
Al-Moisheer AS, Sultan KS, Mousa MN, Mansour MMM.   +3 more
europepmc   +1 more source

Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation

Advanced Intelligent Systems, EarlyView.
Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison, Kevin Nadaud, Josquin Harrison, Guillaume F. Nataf, Laura Bégon‐Lours   +4 more
wiley   +1 more source