Results 191 to 200 of about 27,824 (260)

Polar‐low track prediction using machine‐learning methods

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang   +4 more
wiley   +1 more source

Hybrid physics–data‐driven modeling for sea ice thermodynamics and transfer learning

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Icepack–NN, a machine‐learning‐based hybrid version of the sea‐ice column model Icepack, is developed to correct state‐dependent forecast errors arising from misspecified snow thermodynamics, using neural networks applied online within the physical model.
G. De Cillis   +7 more
wiley   +1 more source

Deep Reinforcement Learning Based Autonomous Decision‐Making for Cooperative Uncrewed Aerial Vehicles: A Search and Rescue Real World Application

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT This paper presents the first end‐to‐end framework that combines guidance, navigation, and centralized task allocation for multiple UAVs performing autonomous search‐and‐rescue (SAR) in GNSS‐denied indoor environments. A twin delayed deep deterministic policy gradient controller is trained with an artificial potential field (APF) reward that ...
Thomas Hickling   +3 more
wiley   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

open access: yesResponsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen   +8 more
wiley   +1 more source

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang   +5 more
wiley   +1 more source

Inferring Brown Bear Hair Snare Interactions by Automatically Detecting Bipedalism on Camera Trap Images Using Pose Estimation and a Multilayer Perceptron

open access: yesRemote Sensing in Ecology and Conservation, EarlyView.
This study proposes an automated method to infer brown bear hair snare interactions by detecting bipedal behavior in camera‐trap images using a pose estimation model and a multilayer perceptron (MLP). A YOLO‐based model, fine‐tuned from humans and dogs to a custom dataset, achieved high performance (≈93% keypoint precision and ≈96% classification ...
Arnau Campanera‐Moliné   +8 more
wiley   +1 more source

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