Gade, K.
* 2015: Impact of ITS on CO2 emissions: the contribution of a standardised assessment framework
Gade, M.
* 2009: Sea Surface Current Fields in the Baltic Sea Derived From Multi-Sensor Satellite Data
* 2014: Automatic Enrichments with Controlled Vocabularies in Europeana: Challenges and Consequences
* 2017: Detection of Bivalve Beds on Exposed Intertidal Flats Using Polarimetric SAR Indicators
* 2017: Fully Polarimetric SAR Imagery Classification Scheme for Mud and Sand Flats in Intertidal Zones, A
* 2021: Classification Scheme for Sediments and Habitats on Exposed Intertidal Flats with Multi-Frequency Polarimetric SAR, A
* 2022: Marine Oil Pollution in an Area of High Economic Use: Statistical Analyses of SAR Data from the Western Java Sea
* 2024: GLUENet: An Efficient Network for Remote Sensing Image Dehazing with Gated Linear Units and Efficient Channel Attention
* 2024: TENet: A Texture-Enhanced Network for Intertidal Sediment and Habitat Classification in Multiband PolSAR Images
Includes: Gade, M. Gäde, M.[Maria] (Maybe also Gaede, M.)Gade, M.[Martin]
8 for Gade, M.
Gade, R.[Rikke]
* 2013: Long-Term Occupancy Analysis Using Graph-Based Optimisation in Thermal Imagery
* 2013: Sports Type Classification Using Signature Heatmaps
* 2014: Improving Global Multi-target Tracking with Local Updates
* 2014: Thermal cameras and applications: a survey
* 2015: Audio-Visual Classification of Sports Types
* 2017: Computer vision for sports: Current applications and research topics
* 2017: Measuring Energy Expenditure in Sports by Thermal Video Analysis
* 2018: Camera Calibration for Underwater 3D Reconstruction Based on Ray Tracing Using Snell's Law
* 2018: Estimating the Number of Soccer Players Using Simulation-Based Occlusion Handling
* 2020: Context-Aware Loss Function for Action Spotting in Soccer Videos, A
* 2020: Multimodal and multiview distillation for real-time player detection on a football field
* 2020: Special issue on Advanced Machine Vision
* 2021: Determining Dendrometry Using Drone Scouting, Convolutional Neural Networks and Point Clouds
Includes: Gade, R.[Rikke] Gade, R.
13 for Gade, R.
Gade, V.R.[Vishal Reddy]
* 2021: Development of Autonomous UVC Disinfectant Robot
Gadea Girones, R.[Rafael]
* 2007: wavelet-VQ system for real-time video compression, A
Includes: Gadea Girones, R.[Rafael] Gadea-Girones, R.[Rafael]
Gadea, O.C.A.[Otto C. A.]
* 2022: Surface Deformation Analysis of the Houston Area Using Time Series Interferometry and Emerging Hot Spot Analysis
Gadek, B.[Bogdan]
* 2023: Quantifying Changes in Extent and Velocity of the Hornbreen/Hambergbreen Glacial System (SW, Spitsbergen) Based on Timeseries of Multispectral Satellite Imagery
Gadekallu, T.R.[Thippa Reddy]
* 2020: Fake Review Classification Using Supervised Machine Learning
* 2020: Predictive model for battery life in IoT networks
* 2022: Identification of malnutrition and prediction of BMI from facial images using real-time image processing and machine learning
* 2022: novel unsupervised ensemble framework using concept-based linguistic methods and machine learning for twitter sentiment analysis, A
* 2023: Data Freshness Optimization Under CAA in the UAV-Aided MECN: A Potential Game Perspective
* 2023: Location Recommendation Based on Mobility Graph With Individual and Group Influences
* 2023: RSSI Map-Based Trajectory Design for UGV Against Malicious Radio Source: A Reinforcement Learning Approach
* 2023: Vision Transformer Approach for Traffic Congestion Prediction in Urban Areas, A
8 for Gadekallu, T.R.
Gadelha, I.[Igor]
* 2023: Hinting Pipeline and Multivariate Regression CNN for Maize Kernel Counting on the Ear
Gadelha, M.[Matheus]
* 2018: Deeper Look at 3D Shape Classifiers, A
* 2018: Multiresolution Tree Networks for 3D Point Cloud Processing
* 2019: Bayesian Perspective on the Deep Image Prior, A
* 2019: Shape Reconstruction Using Differentiable Projections and Deep Priors
* 2020: Inferring 3D Shapes from Image Collections Using Adversarial Networks
* 2020: Label-efficient Learning on Point Clouds Using Approximate Convex Decompositions
* 2020: Learning Generative Models of Shape Handles
* 2021: Deep Manifold Prior
* 2022: PlanarRecon: Realtime 3D Plane Detection and Reconstruction from Posed Monocular Videos
* 2023: 3DMiner: Discovering Shapes from Large-Scale Unannotated Image Datasets
* 2023: Accidental Turntables: Learning 3D Pose by Watching Objects Turn
Includes: Gadelha, M.[Matheus] Gadelha, M.
11 for Gadelha, M.
Gadelha, M.A.[Matheus A.]
* 2014: DRINK: Discrete Robust Invariant Keypoints
Gademann, G.
* 2002: Photogrammetric measurement of patients in radiotherapy
Gademer, A.
* 2015: Dedicated Payloads for Low Altitude Remote Sensing in Natural Environments
Gadepally, V.
* 2010: MATLAB for Signal Processing on Multiprocessors and Multicores
* 2014: Framework for Estimating Driver Decisions Near Intersections, A
Gader, P.[Paul]
* 2008: Prior-updating ensemble learning for discrete HMM
* 2009: Random Set Framework for Context-Based Classification With Hyperspectral Imagery
* 2010: Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning
* 2014: Context dependent hyperspectral subpixel target detection
* 2014: Robust Context Dependent Spectral Unmixing
* 2014: Signal and Image Processing in Hyperspectral Remote Sensing
* 2014: Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing, A
* 2014: Superpixel Estimation for Hyperspectral Imagery
* 2015: Multiple-Instance Hidden Markov Models With Applications to Landmine Detection
* 2016: Hyperspectral Unmixing With Endmember Variability via Alternating Angle Minimization
* 2022: Multitarget Multiple-Instance Learning for Hyperspectral Target Detection
* 2023: HYPSO-1 CubeSat: First Images and In-Orbit Characterization
Includes: Gader, P.[Paul] Gader, P.
12 for Gader, P.
Gader, P.D.
* 1986: Automated Bridge Detection in FLIR Images
* 1990: Image Algebra and Morphological Image Processing
* 1991: Image Algebra and Morphological Image Processing II
* 1991: Recognition of Handwritten Digits Using Template and Model Matching
* 1991: Separable Decompositions and Approximations of Greyscale Morphological Templates
* 1992: Image Algebra and Morphological Image Processing III
* 1992: Local Decomposition of Gray-Scale Morphological Templates
* 1992: Special Issue: Image Algebra and Morphological Image Processing
* 1993: Image Algebra and Morphological Image Processing IV
* 1994: Advances in Fuzzy Integration for Pattern Recognition
* 1994: Image Algebra and Morphological Image Processing V
* 1995: Comparison of Crisp and Fuzzy Character Neural Networks in Handwritten Word Recognition
* 1995: Fuzzy Logic System for the Detection and Recognition of Street Number Fields on Handwritten Postal Addresses, A
* 1995: Handprinted Word Recognition on a NIST Data Set
* 1996: Automatic Feature Generation for Handwritten Digit Recognition
* 1996: Dynamic-Programming-Based Handwritten Word Recognition Using the Choquet Fuzzy Integral as the Match Function
* 1996: Fusion of Handwritten Word Classifiers
* 1996: Handwritten Word Recognition Using Segmentation-Free Hidden Markov Modeling and Segmentation-Based Dynamic-Programming Techniques
* 1996: Hybrid Feature Extraction Framework for Handwritten Numeric Fields Recognition, A
* 1997: Handwritten Word Recognition with Character and Inter-Character Neural Networks
* 1997: Morphological Shared-Weight Networks with Applications to Automatic Target Recognition
* 1997: Neural and Fuzzy Methods in Handwriting Recognition
* 1997: Recognition of Handprinted Numerals in Visa(R) Card Application Forms
* 1998: Data-Driven Homolog Matching for Chromosome Identification
* 1998: Homologue Matching Applications: Recognition of Overlapped Chromosomes
* 1999: Entropy Optimized Morphological Shared-Weight Neural Networks
* 1999: LADAR Scene Description Using Fuzzy Morphology and Rules
* 1999: Lexicon-Driven Handwritten Word Recognition Using Optimal Linear Combinations of Order Statistics
* 1999: Morphological Shared-Weight Neural Networks: A Tool for Automatic Target Recognition Beyond the Visible Spectrum
* 2000: Fuzzy logic detection of landmines with ground penetrating radar
* 2000: LADAR Target Detection Using Morphological Shared-Weight Neural Networks
* 2000: Morphological regularization neural networks
* 2000: Outlier Rejection with MLPs and Variants of RBF Networks
* 2000: Training Neural Networks to Count White Blood Cells Via a Minimum Counting Error Objective Function
* 2001: Fusion of multiple handwritten word recognition techniques
* 2001: Generalizations of Morphological Shared Weight Networks Using Choquet Integrals with Applications to Ground Penetrating Radar Based Land Mine Detection
* 2001: Non-homothetic granulometric mixing theory with application to blood cell counting
* 2002: Feature and decision level sensor fusion of electromagnetic induction and ground penetrating radar sensors for landmine detection with hand-held units
* 2002: linear prediction land mine detection algorithm for hand held ground penetrating radar, A
* 2002: Neural networks with enhanced outlier rejection ability for off-line handwritten word recognition
* 2002: Pattern recognition for humanitarian de-mining
* 2003: Domain learning using Choquet integral-based morphological shared weight neural networks
* 2003: Training DHMMs of mine and clutter to minimize landmine detection errors
* 2004: Discrimination Mode Processing for EMI and GPR Sensors for Hand-Held Land Mine Detection
* 2007: Frequency Subband Processing and Feature Analysis of Forward-Looking Ground-Penetrating Radar Signals for Land-Mine Detection
* 2007: Large-Scale Systematic Evaluation of Algorithms Using Ground-Penetrating Radar for Landmine Detection and Discrimination, A
* 2007: Optimizing the Area Under a Receiver Operating Characteristic Curve With Application to Landmine Detection
* 2008: EK-SVD: Optimized dictionary design for sparse representations
* 2008: Endmember detection using the Dirichlet process
* 2008: Investigation of Using the Spectral Characteristics From Ground Penetrating Radar for Landmine/Clutter Discrimination, An
* 2008: Vegetation Mapping for Landmine Detection Using Long-Wave Hyperspectral Imagery
* 2010: Context-Dependent Multisensor Fusion and Its Application to Land Mine Detection
* 2010: Pattern Recognition Using Functions of Multiple Instances
* 2010: Variational Mixture of Experts for Classification with Applications to Landmine Detection
* 2011: Land-Mine Detection With Ground-Penetrating Radar Using Multistream Discrete Hidden Markov Models
* 2011: Robust kernel discriminant analysis using fuzzy memberships
* 2012: Hyperspectral image analysis with piece-wise convex endmember estimation and spectral unmixing
* 2013: Piecewise Convex Multiple-Model Endmember Detection and Spectral Unmixing
* 2013: Sampling Piecewise Convex Unmixing and Endmember Extraction
* 2016: Spatial Compositional Model for Linear Unmixing and Endmember Uncertainty Estimation, A
* 2017: Nonrigid Registration of Hyperspectral and Color Images with Vastly Different Spatial and Spectral Resolutions for Spectral Unmixing and Pansharpening
* 2018: Gaussian Mixture Model Representation of Endmember Variability in Hyperspectral Unmixing, A
* 2019: Comparison of Methods for Modeling Fractional Cover Using Simulated Satellite Hyperspectral Imager Spectra
* 2020: Integrated Approach to Registration and Fusion of Hyperspectral and Multispectral Images, An
Includes: Gader, P.D. Gader, P.D.[Paul D.]
64 for Gader, P.D.
Gadermayr, M.[Michael]
* 2012: Dual-Resolution Active Contours Segmentation of Vickers Indentation Images with Shape Prior Initialization
* 2012: Image Segmentation of Vickers Indentations Using Shape from Focus
* 2012: Impact of Unfocused Vickers Indentation Images on the Segmentation Performance, The
* 2013: Active contours methods with respect to Vickers indentations
* 2013: Barrel-Type Distortion Compensated Fourier Feature Extraction
* 2013: Distortion Adaptive Image Classification: An Alternative to Barrel-Type Distortion Correction
* 2013: Feature Extraction with Intrinsic Distortion Correction in Celiac Disease Imagery: No Need for Rasterization
* 2013: Problems in Distortion Corrected Texture Classification and the Impact of Scale and Interpolation
* 2013: Shape Curvature Histogram: A Shape Feature for Celiac Disease Diagnosis
* 2014: Degradation adaptive texture classification
* 2014: Degradation Adaptive Texture Classification: A Case Study in Celiac Disease Diagnosis Brings New Insight
* 2014: Getting one step closer to fully automatized celiac disease diagnosis
* 2014: Is a Precise Distortion Estimation Needed for Computer Aided Celiac Disease Diagnosis?
* 2014: Quality Based Information Fusion in Fully Automatized Celiac Disease Diagnosis
* 2014: Scale-Adaptive Texture Classification
* 2015: Boosting Small-Data Performance of LBP: A Case Study in Celiac Disease Diagnosis
* 2015: How to exploit large image data in the fields of texture classification: A case study with local binary patterns
* 2016: Do We Need Large Annotated Training Data for Detection Applications in Biomedical Imaging? A Case Study in Renal Glomeruli Detection
* 2016: Domain Adaptive Classification for Compensating Variability in Histopathological Whole Slide Images
* 2016: Evaluation of i-Scan Virtual Chromoendoscopy and Traditional Chromoendoscopy for the Automated Diagnosis of Colonic Polyps
* 2016: Incorporating human knowledge in automated celiac disease diagnosis
* 2017: Fully-Automated CNN-Based Computer Aided Celiac Disease Diagnosis
* 2017: Quantitative Assessment of Image Normalization for Classifying Histopathological Tissue of the Kidney, A
* 2019: Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology
* 2022: Evaluation of Multi-Scale Multiple Instance Learning to Improve Thyroid Cancer Classification
Includes: Gadermayr, M.[Michael] Gadermayr, M.
25 for Gadermayr, M.
Gadeski, E.[Etienne]
* 2017: Vision-language integration using constrained local semantic features
* 2018: GPU deformable part model for object recognition