Bort, J.[Jordi]
* 2019: Use of RGB Vegetation Indexes in Assessing Early Effects of Verticillium Wilt of Olive in Asymptomatic Plants in High and Low Fertility Scenarios
Bortfeld, H.[Heather]
* 2008: Reducing the other-race effect through caricatures
Borth, D.[Damian]
* 2011: Lookapp: interactive construction of web-based concept detectors
* 2012: Linking visual concept detection with viewer demographics
* 2013: Content analysis meets viewers: linking concept detection with demographics on YouTube
* 2018: What do Deep Networks Like to See?
* 2019: Multi-Task Learning for Segmentation of Building Footprints with Deep Neural Networks
* 2022: Self-supervised Vision Transformers for Land-cover Segmentation and Classification
* 2023: Masked Vision Transformers for Hyperspectral Image Classification
* 2023: Sparse Multimodal Vision Transformer for Weakly Supervised Semantic Segmentation
Includes: Borth, D.[Damian] Borth, D.
8 for Borth, D.
Borth, D.J.[David J.]
* 2022: Robust Gaussian process regression with a bias model
Bortnik, J.[Jacob]
* 2023: Deep Learning Driven Detection of Tsunami Related Internal Gravity Waves: a path towards open-ocean natural hazards detection
Bortolan, G.
* 1996: Fuzzy Pattern-Classification and the Connectionist Approach
Bortolas, N.[Natalia]
* 2022: QDA-System: A Cloud-Based System for Monitoring Water Quality in Brazilian Hydroelectric Reservoirs from Space
Includes: Bortolas, N.[Natalia] Bortolas, N.[Natália]
Bortolaso, C.[Christophe]
* 2022: Intelligent Document Processing with Small and Relevant Training Dataset
Bortolato, B.
* 2020: Learning privacy-enhancing face representations through feature disentanglement
Bortoli, D.
* 2014: Vertical Distribution of Lower Tropospheric NO2 Derived From Diffuse Solar Radiation Measurements: A Geometrical Retrieval Approach
* 2022: Analysis of NO2 and O3 Total Columns from DOAS Zenith-Sky Measurements in South Italy
* 2022: Editorial for the Special Issue Air Quality Research Using Remote Sensing
* 2022: Numerical Weather Predictions and Re-Analysis as Input for Lidar Inversions: Assessment of the Impact on Optical Products
Includes: Bortoli, D. Bortoli, D.[Daniele]
Bortolini, M.C.[Maria Catira]
* 2017: Automatic ear detection and feature extraction using Geometric Morphometrics and convolutional neural networks
Bortolon, M.[Matteo]
* 2023: MONET dataset: Multimodal drone thermal dataset recorded in rural scenarios, The
* 2023: VM-NERF: Tackling Sparsity in NeRF with View Morphing
Bortolot, Z.J.[Zachary J.]
* 2005: Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data
* 2006: Using Tree Clusters to Derive Forest Properties from Small Footprint Lidar Data
Bortolotti, C.[Claudio]
* 2024: Toward a European Facility for Ground-Based Radar Observations of Near-Earth Objects
Bortolotto, S.
* 2019: diagnostic Survey: A Methodology for the Knowledge of A Complex Architectural Palimpsest, The
Bortolozzi, F.
* 1996: fuzzy ARTMAP-based classification system for detecting cancerous cells, based on the one-class problem approach, A
* 1996: Results of the Use of Bayesian Classifiers for Identification of Breast Cancer Cell Nuclei
* 2000: New Segmentation Approach for Handwritten Digits, A
* 2001: Handwritten isolated word recognition: an approach based on Mutual Information for feature set validation
* 2001: Handwritten month word recognition on Brazilian bank cheques
* 2001: modular system to recognize numerical amounts on Brazilian bank cheques, A
* 2001: Off-line signature verification using HMM for random, simple and skilled forgeries
* 2001: Two-Stage HMM-Based System for Recognizing Handwritten Numeral Strings, A
* 2002: Distinguishing between Handwritten and Machine Printed Text in Bank Cheque Images
* 2002: Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition
* 2002: Segmentation and recognition of handwritten dates
* 2002: string length predictor to control the level building of HMMs for handwritten numeral recognition, A
* 2003: Complementary features combined in an HMM-based system to recognize handwritten digits
* 2003: Feature selection for ensembles: A hierarchical multi-objective genetic algorithm approach
* 2003: Impacts of verification on a numeral string recognition system
* 2003: recognition and verification strategy for handwritten word recognition, A
* 2003: recognition of handwritten numeral strings using a two-stage HMM-based method, The
* 2003: Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
* 2004: Segmentation and recognition of handwritten dates: An HMM-MLP hybrid approach
* 2005: comparison of SVM and HMM classifiers in the off-line signature verification, A
* 2006: Handwritten Artefact Identification Method for Table Interpretation with Little Use of Previous Knowledge
* 2013: Feature Selection for Forensic Handwriting Identification
* 2017: Forensic Document Examination: Who Is the Writer?
Includes: Bortolozzi, F. Bortolozzi, F.[Flávio] Bortolozzi, F.[Flavio]
23 for Bortolozzi, F.
Bortoluzzi, D.
* 2020: On Reliable Neural Network Sensorimotor Control in Autonomous Vehicles
* 2022: Application of LISA Gravitational Reference Sensor Hardware to Future Intersatellite Geodesy Missions
Includes: Bortoluzzi, D. Bortoluzzi, D.[Daniele]
Bortoluzzi, M.[Maria]
* 2008: Towards a Framework of Critical Multimodal Analysis: Emotion in a Film Trailer
Borton, D.A.[David A.]
* 2021: Facial Action Units and Head Dynamics in Longitudinal Interviews Reveal OCD and Depression severity and DBS Energy
Bortsova, G.[Gerda]
* 2016: Mitosis Detection in Intestinal Crypt Images with Hough Forest and Conditional Random Fields
* 2018: Deep Multi-instance Volumetric Image Classification with Extreme Value Distributions
* 2020: Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem
Includes: Bortsova, G.[Gerda] Bortsova, G.
Bortz, B.
* 2014: Exploring the integrality and separability of the Leap Motion Controller for direct manipulation 3D interaction
Bortz, M.[Michael]
* 2021: Adaptive Sampling of Pareto Frontiers with Binary Constraints Using Regression and Classification