Results 101 to 110 of about 22,874 (259)

Nonparametric Modelling of Ship Dynamics Using Puma Optimizer Algorithm-Optimized Twin Support Vector Regression

open access: yesJournal of Marine Science and Engineering
Ship dynamic models serve as the foundation for designing ship controllers, trajectory planning, and obstacle avoidance. Support vector regression (SVR) is a commonly used nonparametric modelling method for ship dynamics.
Lichao Jiang   +4 more
doaj   +1 more source

Moving Object Detection for Dynamic Background Scenes Based on Spatiotemporal Model

open access: yesAdvances in Multimedia, 2017
Moving object detection in video streams is the first step of many computer vision applications. Background modeling and subtraction for moving detection is the most common technique for detecting, while how to detect moving objects correctly is still a ...
Yizhong Yang   +4 more
doaj   +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 and Robust Methods

open access: yesComputational Statistics & Data Analysis, 2007
Rand R. Wilcox   +3 more
openaire   +2 more sources

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

Estimation of Value at Risk : Extreme Value and Robust Approaches

open access: yesOperations Research and Decisions, 2010
The large portfolios of traded assets held by many financial institutions have made the measurement of market risk a necessity. In practice, VaR measures are computed for several holding periods and confidence levels.
Grażyna Trzpiot, Justyna Majewska
doaj  

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

MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

open access: yesJournal of Statistical Software, 2011
MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching methods.
Daniel Ho   +3 more
doaj  

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