Laus, F.
* 2014: Second Order Differences of Cyclic Data and Applications in Variational Denoising
* 2016: Transport Between RGB Images Motivated by Dynamic Optimal Transport
* 2017: Nonlocal Denoising Algorithm for Manifold-Valued Images Using Second Order Statistics, A
* 2017: Optimal Transport for Manifold-Valued Images
* 2018: Nonlocal Myriad Filters for Cauchy Noise Removal
* 2019: Multivariate Myriad Filters Based on Parameter Estimation of Student-t Distributions
Includes: Laus, F. Laus, F.[Friederike]
Lausch, A.[Angela]
* 2012: Scale-specific Hyperspectral Remote Sensing Approach in Environmental Research
* 2014: Extraction of Plant Physiological Status from Hyperspectral Signatures Using Machine Learning Methods
* 2014: Reduction of Uncorrelated Striping Noise: Applications for Hyperspectral Pushbroom Acquisitions
* 2015: Gradient-Based Assessment of Habitat Quality for Spectral Ecosystem Monitoring
* 2015: Mapping the Spectral Soil Quality Index (SSQI) Using Airborne Imaging Spectroscopy
* 2015: Spectral Unmixing of Forest Crown Components at Close Range, Airborne and Simulated Sentinel-2 and EnMAP Spectral Imaging Scale
* 2016: Imagine All the Plants: Evaluation of a Light-Field Camera for On-Site Crop Growth Monitoring
* 2016: In Situ/Remote Sensing Integration to Assess Forest Health: A Review
* 2016: Understanding Forest Health with Remote Sensing -Part I: A Review of Spectral Traits, Processes and Remote-Sensing Characteristics
* 2017: Understanding Forest Health with Remote Sensing-Part II: A Review of Approaches and Data Models
* 2018: Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches
* 2019: Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity: Part I: Soil Characteristics
* 2019: Mapping of Soil Total Nitrogen Content in the Middle Reaches of the Heihe River Basin in China Using Multi-Source Remote Sensing-Derived Variables
* 2020: Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity: Part II: Geomorphology, Terrain and Surfaces
* 2021: Inferring Grassland Drought Stress with Unsupervised Learning from Airborne Hyperspectral VNIR Imagery
* 2021: Mapping European Spruce Bark Beetle Infestation at Its Early Phase Using Gyrocopter-Mounted Hyperspectral Data and Field Measurements
* 2022: Remote Sensing of Geomorphodiversity Linked to Biodiversity: Part III: Traits, Processes and Remote Sensing Characteristics
* 2024: Ecosystem Integrity Remote Sensing - Modelling and Service Tool - ESIS/Imalys
18 for Lausch, A.
Lausen, B.[Berthold]
* 2003: Double-bagging: combining classifiers by bootstrap aggregation
Lausen, R.[Ralph]
* 2018: Highly efficient image registration for embedded systems using a distributed multicore DSP architecture
Lausser, L.[Ludwig]
* 2014: Unlabeling data can improve classification accuracy
* 2020: Introducing Bidirectional Ordinal Classifier Cascades Based on a Pain Intensity Recognition Scenario