Results 151 to 160 of about 128,596 (295)

Testing for symmetric error distribution in nonparametric regression models [PDF]

open access: yes
For the problem of testing symmetry of the error distribution in a nonparametric regression model we propose as a test statistic the difference between the two empirical distribution functions of estimated residuals and their counterparts with opposite ...
Neumeyer, Natalie, Dette, Holger
core  

Spatially Informed Feature Selection and Machine Learning in Matrix‐Assisted Laser Desorption/Ionization Imaging for Cohort‐Scale Molecular Tissue Phenomics in Glioblastoma

open access: yesAdvanced Intelligent Discovery, EarlyView.
Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed   +15 more
wiley   +1 more source

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

open access: yesAdvanced 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   +5 more
wiley   +1 more source

Nonparametric estimation of concave production technologies by entropic methods [PDF]

open access: yes
An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production ...
Alex Shapiro   +4 more
core  

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

Resource‐Aware Contrastive Scattering Meta‐Learning for Efficient Few‐Shot Acoustic Anomaly Detection

open access: yesAdvanced Intelligent Systems, EarlyView.
This paper introduces a resource‐aware Contrastive Scattering Meta‐Learning (CSML) framework for acoustic anomaly detection. By leveraging training‐free wavelet scattering and metric‐based meta‐learning, the model achieves competitive performance with only 50 K learnable parameters—a 98% reduction compared to state‐of‐the‐art frameworks—enabling ...
Rami Zewail, Bassem Mokhtar
wiley   +1 more source

Xstainer: A Novel Virtual Staining Tool Powered by Advanced Deep Learning Techniques

open access: yesAdvanced Intelligent Systems, EarlyView.
Xstainer is a deep learning–based virtual staining framework that converts hematoxylin and eosin‐stained whole slide images into multiple histochemical stains, including Masson's trichrome, Periodic acid‐Schiff, Jones methenamine silver, and Toluidine blue.
Fatma Nur Kinali   +15 more
wiley   +1 more source

Accounting for animal health in efficiency analysis: An application to Swedish dairy farms

open access: yesAmerican Journal of Agricultural Economics, EarlyView.
Abstract Poor animal health is a central concern in modern livestock production. Despite the necessity to incorporate animal health in efficiency analysis, the theoretical and empirical developments are limited on this subject. This article appropriately characterizes the axiomatic properties of animal health within a production framework.
Frederic Ang   +3 more
wiley   +1 more source

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