Results 61 to 70 of about 5,063,949 (192)

Multi-Target Tracking for SMARTnet: Multi-Layer Probability Hypothesis Filter for Near-Earth Object Tracking [PDF]

, 2021
In this paper, a modified version of the finite set statistics-based Probability Hypothesis Density (PHD) filter is developed specifically for the optical multi-target tracking of objects in the near-Earth realm for Space Situational Awareness (SAA).
Fiedler, H., Schildknecht, Thomas, Frueh, C., Schildknecht, T., Fiedler, Hauke, Herzog, J., Herzog, Johannes, Frueh, Carolin   +7 more
core   +2 more sources

"Spooky action at a distance" in the cardinalized probability hypothesis density filter

, 2022
S.1657-1664The cardinalized probability hypothesis density (CPHD) filter is a recursive Bayesian algorithm for estimating multiple target states with varying target number in clutter.
Franken, D., Schmidt, M., Ulmke, M.
core   +1 more source

How to report neurotechnology and artificial intelligence studies in epilepsy: Peer‐review‐inspired recommendations

Epilepsia Open, EarlyView.
Abstract Objective The integration of neurotechnology and artificial intelligence (AI) in epilepsy research has led to significant advancements in diagnosis, monitoring, and treatment. However, the impact of these innovations is often diminished by inadequate and inaccurate reporting, limiting their reproducibility and implementation.
Pedro F. Viana, Matthew McWilliam, Andrea Biondi, Jesus Servando Medel‐Matus, Naoto Kuroda, Giulia Sofia Cereda, Aristea S. Galanopoulou   +6 more
wiley   +1 more source

A Comprehensive Study to Compare Different Compound Representations for Predicting Carcinogenicity In Vivo

Journal of Applied Toxicology, EarlyView.
ABSTRACT Carcinogenicity evaluation is a critical component of chemical risk assessment, yet traditional in vivo testing remains time consuming, costly, and ethically challenging. Computational approaches based on machine learning offer promising alternatives, but the relative contributions of different molecular representation strategies for ...
Iuri Barbosa Pereira, Rogerio Salvini, Eloisa Dutra Caldas   +2 more
wiley   +1 more source

Adaptive grid‐driven probability hypothesis density filter for multi‐target tracking

IET Signal Processing, 2021
The probability hypothesis density (PHD) filter and its cardinalised version PHD (CPHD) have been demonstratedasa class of promising algorithms for multi‐target tracking (MTT) with unknown,time‐varying number of targets.
Jinlong Yang, Jiuliu Tao, Yuan Zhang
doaj   +1 more source

Fragmentation Across Scales, Geography, and Climate Challenges in European Urban Climate Change Adaptation and Mitigation Research: A Bibliometric and Systematic Review

Sustainable Development, EarlyView.
ABSTRACT European urban climate change research lacks integration across scales, geography, and climate challenges, despite Europe's coordinated policy frameworks. Through a hybrid bibliometric and systematic review of 1528 studies (2010–2025) using Cortext Manager and PRISMA 2020 guidelines, this study maps the conceptual patterns, knowledge gaps, and
Isabela Pichardo‐Velázquez, Richard Dean Morales, Antonino Marvuglia   +2 more
wiley   +1 more source

Cooperative Localization for Multi-AUVs Based on GM-PHD Filters and Information Entropy Theory

Sensors, 2017
Cooperative localization (CL) is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs).
Lichuan Zhang, Tonghao Wang, Feihu Zhang, Demin Xu   +3 more
doaj   +1 more source

A probability hypothesis density filter for tracking non‐rigid extended targets using spatiotemporal Gaussian process model

IET Signal Processing, 2022
This paper proposes a random finite set (RFS)‐based algorithm to deal with the tracking problem of multiple non‐rigid extended targets (MNRET) with irregular shapes in the presence of clutter, false alarms and missed detection.
Sunyong Wu, Yusong Zhou, Yun Xie, Qiutiao Xue   +3 more
doaj   +1 more source

Gaussian mixture probability hypothesis density filter against measurement origin uncertainty

, 2020
The Gaussian mixture probability hypothesis density (GM-PHD) filter is a promising solution to the multi-target tracking (MU) problem, which successfully integrates target detection, tracking, and identification.
Kwon, Cheolhyeon, Kim, Dohyeung, Hwang, Inseok   +2 more
core   +1 more source

Fine‐scale spatio‐temporal niche partitioning enables coexistence of wild ungulates and livestock in a resource‐limited Himalayan landscape, India

Wildlife Biology, EarlyView.
Understanding how wild ungulates share space with domestic livestock is central to conservation planning in Himalayan multi‐use landscapes. This study focuses on multi‐axis niche relationships among six wild ungulates: hangul Cervus hanglu hanglu, Kashmir musk deer Moschus cupreus, Himalayan goral Naemorhedus goral, kashmir markhor Capra falconeri ...
Mohsin Javid, Khursheed Ahmad, Orus Ilyas   +2 more
wiley   +1 more source