UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

Water (Basel), 2020-12, Vol.12 (12), p.3399

2020

Volltextzugriff (PDF)

A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery

Remote sensing of environment, 2019-11, Vol.233, p.111350, Article 111350

2019

Volltextzugriff (PDF)

Drone-borne sensing of major and accessory pigments in algae using deep learning modeling

GIScience and remote sensing, 2022-12, Vol.59 (1), p.310-332

2022

Volltextzugriff (PDF)

Deep learning-based mapping of total suspended solids in rivers across South Korea using high resolution satellite imagery

GIScience and remote sensing, 2024-12, Vol.61 (1)

2024

Volltextzugriff (PDF)

Enhancing Machine Learning Performance in Estimating CDOM Absorption Coefficient via Data Resampling

Remote sensing (Basel, Switzerland), 2024-07, Vol.16 (13), p.2313

2024

Volltextzugriff (PDF)

Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir

International journal of applied earth observation and geoinformation, 2022-11, Vol.114, p.103053, Article 103053

2022

Volltextzugriff (PDF)

Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery

GIScience and remote sensing, 2022-12, Vol.59 (1), p.547-567

2022

Volltextzugriff (PDF)

Generalization of U-Net Semantic Segmentation for Forest Change Detection in South Korea Using Airborne Imagery

Forests, 2022-12, Vol.13 (12), p.2170

2022

Volltextzugriff (PDF)

Deep learning-based super-resolution for harmful algal bloom monitoring of inland water

GIScience and remote sensing, 2023-12, Vol.60 (1)

2023

Volltextzugriff (PDF)

Long short-term memory models of water quality in inland water environments

Water research X, 2023-12, Vol.21, p.100207-100207, Article 100207

2023

Volltextzugriff (PDF)

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Remote sensing (Basel, Switzerland), 2020-04, Vol.12 (7), p.1073

2020

Volltextzugriff (PDF)

Comparative Studies of Different Imputation Methods for Recovering Streamflow Observation

Water (Basel), 2015-12, Vol.7 (12), p.6847-6860

2015

Volltextzugriff (PDF)

Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models

Water research X, 2024-05, Vol.23, p.100228, Article 100228

2024

Volltextzugriff (PDF)

Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach

Remote sensing (Basel, Switzerland), 2022-04, Vol.14 (7), p.1754

2022

Volltextzugriff (PDF)

Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

Frontiers in Marine Science, 2021-10, Vol.8

2021

Volltextzugriff (PDF)

Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Remote sensing (Basel, Switzerland), 2021-02, Vol.13 (4), p.709

2021

Volltextzugriff (PDF)

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Remote sensing (Basel, Switzerland), 2017-06, Vol.9 (6), p.542

2017

Volltextzugriff (PDF)

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Water (Basel), 2018-08, Vol.10 (8), p.1020

2018

Volltextzugriff (PDF)

Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil

The Science of the total environment, 2020-11, Vol.741, p.140162-140162, Article 140162

2020

Volltextzugriff (PDF)

Classifying eutrophication spatio-temporal dynamics in river systems using deep learning technique

The Science of the total environment, 2024-12, Vol.954, p.176585, Article 176585

2024

Volltextzugriff (PDF)

Machine learning-derived dose-response relationships considering interactions in mixtures: Applications to the oxidative potential of particulate matter

Journal of hazardous materials, 2024-08, Vol.475, p.134864, Article 134864

2024

Volltextzugriff (PDF)

Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage

Water research (Oxford), 2021-09, Vol.203, p.117483, Article 117483

2021

Volltextzugriff (PDF)

Using convolutional neural network for predicting cyanobacteria concentrations in river water

Water research (Oxford), 2020-11, Vol.186, p.116349-116349, Article 116349

2020

Volltextzugriff (PDF)

Drone-based hyperspectral remote sensing of cyanobacteria using vertical cumulative pigment concentration in a deep reservoir

Remote sensing of environment, 2020-01, Vol.236, p.111517, Article 111517

2020

Volltextzugriff (PDF)

Estimation of aquatic ecosystem health using deep neural network with nonlinear data mapping

Ecological informatics, 2024-07, Vol.81, p.102588, Article 102588

2024

Volltextzugriff (PDF)

1 – 25 von 53

Suche als RSS-Feed

Suchergebnisse filtern

Filter anzeigen

Nur zeigen

Geprüft (Peer-Review)
(44)
Mit Volltextzugriff
(50)

Publikationsform

Artikel
(53)

Sprache

Englisch
(53)

Erscheinungsjahr

n.n

Thema

Science & Technology
(47)
Life Sciences & Biomedicine
(37)
Environmental Sciences & Ecology
(35)
Environmental Sciences
(34)
Technology
(33)
Physical Sciences
(27)
Engineering
(20)
Engineering, Environmental
(17)
Water Resources
(17)
Remote Sensing
(15)
Convolutional Neural Network
(11)
Cyanobacteria
(11)
Deep Learning
(11)
Water Quality
(11)
Algae
(9)
Algorithms
(8)
Geology
(8)
Geosciences, Multidisciplinary
(8)
Imaging Science & Photographic Technology
(8)
Machine Learning
(8)

15 weitere anzeigen...

Weniger anzeigen...

Neu hinzugefügt

... seit 90 Tagen
(2)

Menü

Weitere Dienste

Einstellungen

Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery

Drone-borne sensing of major and accessory pigments in algae using deep learning modeling

Deep learning-based mapping of total suspended solids in rivers across South Korea using high resolution satellite imagery

Enhancing Machine Learning Performance in Estimating CDOM Absorption Coefficient via Data Resampling

Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir

Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery

Generalization of U-Net Semantic Segmentation for Forest Change Detection in South Korea Using Airborne Imagery

Deep learning-based super-resolution for harmful algal bloom monitoring of inland water

Long short-term memory models of water quality in inland water environments

An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery

Comparative Studies of Different Imputation Methods for Recovering Streamflow Observation

Spatiotemporal estimation of groundwater and surface water conditions by integrating deep learning and physics-based watershed models

Optimal Band Selection for Airborne Hyperspectral Imagery to Retrieve a Wide Range of Cyanobacterial Pigment Concentration Using a Data-Driven Approach

Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model

Sensitivity Analysis and Optimization of a Radiative Transfer Numerical Model for Turbid Lake Water

Optimizing Semi-Analytical Algorithms for Estimating Chlorophyll-a and Phycocyanin Concentrations in Inland Waters in Korea

Monitoring Coastal Chlorophyll-a Concentrations in Coastal Areas Using Machine Learning Models

Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil

Classifying eutrophication spatio-temporal dynamics in river systems using deep learning technique

Machine learning-derived dose-response relationships considering interactions in mixtures: Applications to the oxidative potential of particulate matter

Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage

Using convolutional neural network for predicting cyanobacteria concentrations in river water

Drone-based hyperspectral remote sensing of cyanobacteria using vertical cumulative pigment concentration in a deep reservoir

Estimation of aquatic ecosystem health using deep neural network with nonlinear data mapping

Suchergebnisse filtern