Foodeei, N.
* 1994: Coding image sequence intensities along motion trajectories using EC-CELP quantization
Foody, G.[Giles]
* 2016: Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information
* 2016: Geographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information
* 2016: Investigating the Feasibility of Geo-Tagged Photographs as Sources of Land Cover Input Data
* 2018: Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data
* 2020: Use of Automated Change Detection and VGI Sources for Identifying and Validating Urban Land Use Change
* 2021: Scrutinizing Relationships between Submarine Groundwater Discharge and Upstream Areas Using Thermal Remote Sensing: A Case Study in the Northern Persian Gulf
Includes: Foody, G.[Giles] Foody, G.
Foody, G.M.
* 1996: Incorporating Mixed Pixels in the Training, Allocation and Testing Stages of Supervised Classifications
* 1998: Sharpening Fuzzy Classification Output to Refine the Representation of Sub-Pixel Land-Cover Distribution
* 1999: Continuum of Classification Fuzziness in Thematic Mapping, The
* 1999: significance of border training patterns in classification by a feedforward neural network using back propagation learning, The
* 2002: Role of Soft Classification Techniques in the Refinement of Estimates of Ground Control Point Location, The
* 2004: Relative Evaluation of Multiclass Image Classification by Support Vector Machines, A
* 2004: Toward intelligent training of supervised image classifications: Directing training data acquisition for SVM classification
* 2007: One-Class Classification for Mapping a Specific Land-Cover Class: SVDD Classification of Fenland
* 2007: Variability in Soft Classification Prediction and Its Implications for Sub-pixel Scale Change Detection and Super Resolution Mapping
* 2010: Feature Selection for Classification of Hyperspectral Data by SVM
* 2010: Super-Resolution Mapping of Landscape Objects from Coarse Spatial Resolution Imagery
* 2012: Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions
* 2012: Latent Class Modeling for Site- and Non-Site-Specific Classification Accuracy Assessment Without Ground Data
* 2015: Impacts of Species Misidentification on Species Distribution Modeling with Presence-Only Data
* 2016: Assessing a Temporal Change Strategy for Sub-Pixel Land Cover Change Mapping from Multi-Scale Remote Sensing Imagery
* 2016: Iterative Interpolation Deconvolution Algorithm for Superresolution Land Cover Mapping, An
* 2016: Learning-Based Superresolution Land Cover Mapping
* 2016: Sensitivity of Mapping Methods to Reference Data Quality: Training Supervised Image Classifications with Imperfect Reference Data, The
* 2016: Superresolution Land-Cover Change Detection Method Using Remotely Sensed Images With Different Spatial Resolutions, A
* 2017: Impervious Surface Change Mapping with an Uncertainty-Based Spatial-Temporal Consistency Model: A Case Study in Wuhan City Using Landsat Time-Series Datasets from 1987 to 2016
* 2017: Monitoring Thermal Pollution in Rivers Downstream of Dams with Landsat ETM+ Thermal Infrared Images
* 2018: Slavery from Space: Demonstrating the role for satellite remote sensing to inform evidence-based action related to UN SDG number 8
* 2019: Earth Observation and Machine Learning to Meet Sustainable Development Goal 8.7: Mapping Sites Associated with Slavery from Space
* 2019: Spatial-Temporal Super-Resolution Land Cover Mapping With a Local Spatial-Temporal Dependence Model
* 2020: Monitoring surface water area variations of reservoirs using daily MODIS images by exploring sub-pixel information
* 2020: Spatio-Temporal Sub-Pixel Land Cover Mapping of Remote Sensing Imagery Using Spatial Distribution Information From Same-Class Pixels
* 2021: Detection of Spatial and Temporal Patterns of Liana Infestation Using Satellite-Derived Imagery
* 2021: Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification From VHR Imagery
* 2021: Object-Based Area-to-Point Regression Kriging for Pansharpening
* 2021: Spatiotemporal Fusion of Land Surface Temperature Based on a Convolutional Neural Network
* 2022: Global and Local Assessment of Image Classification Quality on an Overall and Per-Class Basis without Ground Reference Data
* 2023: Spectral Characteristics of Beached Sargassum in Response to Drying and Decay over Time
Includes: Foody, G.M. Foody, G.M.[Giles M.]
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