Ignaccolo, M.[Matteo]
* 2019: Mapping with Stakeholders: An Overview of Public Participatory GIS and VGI in Transport Decision-Making
* 2021: Linking Public Transport User Satisfaction with Service Accessibility for Sustainable Mobility Planning
Ignacio San Jose, I.
* 2013: Open Source Software Platform for Visualizing and Teaching Conservation Tasks in Architectural Heritage Environments, An
Ignacio, M.T.
* 2016: Nationwide Natural Resource Inventory Of The Philippines Using Lidar: Strategies, Progress, And Challenges
Ignacio, S.A.[Sergio Aparecido]
* 2006: Handwritten Artefact Identification Method for Table Interpretation with Little Use of Previous Knowledge
Includes: Ignacio, S.A.[Sergio Aparecido] Ignácio, S.A.[Sérgio Aparecido]
Ignakov, D.
* 2010: Near-Optimal Selection of Views and Surface Regions for ICP Pose Estimation
Ignar, S.[Stefan]
* 2020: Remotely Sensed Land Surface Temperature-Based Water Stress Index for Wetland Habitats
Ignashov, P.[Pavel]
* 2023: Spatial Analysis of Vegetation Cover and Permafrost Degradation for a Subarctic Palsa Mire Based on UAS Photogrammetry and GPR Data in the Kola Peninsula, The
Ignasiak, K.[Krystian]
* 1997: Local subspace method for pattern recognition
* 1999: Invariant Reference Points Methodology and Applications
Ignasov, J.[Jevgeni]
* 2023: Proactive Control for Online Individual User Adaptation in a Welfare Robot Guidance Scenario: Toward Supporting Elderly People
Ignat, A.[Anca]
* 2015: Combining Features for Texture Analysis
Ignat, O.[Oana]
* 2024: Augment the Pairs: Semantics-Preserving Image-Caption Pair Augmentation for Grounding-Based Vision and Language Models
Ignatavicius, G.[Gytautas]
* 2022: Influence of Landscape Structure on Wildlife-Vehicle Collisions: Geostatistical Analysis on Hot Spot and Habitat Proximity Relations, The
Ignatenko, A.
* 2002: Depth image-based representations for static and animated 3D objects
* 2004: Depth Image-Based Representation and Compression for Static and Animated 3-D Objects
* 2007: Interactive Image-Based Urban Modelling
Ignateva, O.[Olesia]
* 2024: Conceptualizing and Validating the Trustworthiness of Maps through an Empirical Study on the Influence of Cultural Background on Map Design Perception
Ignatiev, V.[Vladimir]
* 2021: Object-Based Augmentation for Building Semantic Segmentation: Ventura and Santa Rosa Case Study
* 2022: Augmentation-Based Methodology for Enhancement of Trees Map Detalization on a Large Scale
* 2022: Survey of Computer Vision Techniques for Forest Characterization and Carbon Monitoring Tasks, A
Ignatiev, V.M.[Virgily Michailovich]
* 1997: On Time Aspects of an Image Processing in MIMD Computers
Ignatious, H.[Henry]
* 2023: Level-5 Autonomous Driving: Are We There Yet? A Review of Research Literature
Ignatiuk, D.[Dariusz]
* 2019: Quality Assessment and Glaciological Applications of Digital Elevation Models Derived from Space-Borne and Aerial Images over Two Tidewater Glaciers of Southern Spitsbergen
* 2021: SIOS's Earth Observation (EO), Remote Sensing (RS), and Operational Activities in Response to COVID-19
* 2023: Changes in the Structure of the Snow Cover of Hansbreen (S Spitsbergen) Derived from Repeated High-Frequency Radio-Echo Sounding
* 2023: Comparison of Three Methods for Distinguishing Glacier Zones Using Satellite SAR Data
Ignatius, A.R.[Amber R.]
* 2014: Small Reservoir Distribution, Rate of Construction, and Uses in the Upper and Middle Chattahoochee Basins of the Georgia Piedmont, USA, 1950-2010
Ignatius, J.
* 2015: Exchange rate and interest rate differential: A conundrum re-examined via wavelet analysis
Ignatov, A.
* 2013: Estimation of Detector Biases in MODIS Thermal Emissive Bands
* 2014: Reef-Scale Thermal Stress Monitoring of Coral Ecosystems: New 5-km Global Products from NOAA Coral Reef Watch
* 2016: AVHRR GAC SST Reanalysis Version 1 (RAN1)
* 2016: Improved VIIRS and MODIS SST Imagery
* 2016: Preliminary Inter-Comparison between AHI, VIIRS and MODIS Clear-Sky Ocean Radiances for Accurate SST Retrievals
* 2016: Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands
* 2017: DSLR-Quality Photos on Mobile Devices with Deep Convolutional Networks
* 2018: AI Benchmark: Running Deep Neural Networks on Android Smartphones
* 2018: Fast Perceptual Image Enhancement
* 2018: PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report
* 2018: WESPE: Weakly Supervised Photo Enhancer for Digital Cameras
* 2019: AI Benchmark: All About Deep Learning on Smartphones in 2019
* 2019: AIM 2019 Challenge on Bokeh Effect Synthesis: Methods and Results
* 2019: AIM 2019 Challenge on RAW to RGB Mapping: Methods and Results
* 2019: Improving the Calibration of Suomi NPP VIIRS Thermal Emissive Bands During Blackbody Warm-Up/Cool-Down
* 2019: Optimization of Sensitivity of GOES-16 ABI Sea Surface Temperature by Matching Satellite Observations with L4 Analysis
* 2020: Controlling information capacity of binary neural network
* 2020: Rendering Natural Camera Bokeh Effect with Deep Learning
* 2020: Replacing Mobile Camera ISP with a Single Deep Learning Model
* 2021: Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System, A
* 2021: Fast and Accurate Camera Scene Detection on Smartphones
* 2021: Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
* 2021: Fast and Accurate Single-Image Depth Estimation on Mobile Devices, Mobile AI 2021 Challenge: Report
* 2021: Fast Camera Image Denoising on Mobile GPUs with Deep Learning, Mobile AI 2021 Challenge: Report
* 2021: Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report
* 2021: Metop First Generation AVHRR FRAC SST Reanalysis Version 1
* 2021: Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
* 2021: Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report
* 2022: AVHRR GAC Sea Surface Temperature Reanalysis Version 2
* 2022: Efficient and Accurate Quantized Image Super-Resolution on Mobile Npus, Mobile Ai & Aim 2022 Challenge: Report
* 2022: Efficient Single-image Depth Estimation on Mobile Devices, Mobile Ai & Aim 2022 Challenge: Report
* 2022: JPSS VIIRS SST Reanalysis Version 3
* 2022: LAN: Lightweight Attention-based Network for RAW-to-RGB Smartphone Image Processing
* 2022: Learned Smartphone ISP on Mobile GPUS with Deep Learning, Mobile Ai & AIM 2022 Challenge: Report
* 2022: Microisp: Processing 32mp Photos on Mobile Devices with Deep Learning
* 2022: PhoneDepth: A Dataset for Monocular Depth Estimation on Mobile Devices
* 2022: Power Efficient Video Super-resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report
* 2022: PyNet-V2 Mobile: Efficient On-Device Photo Processing With Neural Networks
* 2022: Realistic Bokeh Effect Rendering on Mobile GPUs, Mobile Ai & Aim 2022 Challenge: Report
* 2023: NOAA MODIS SST Reanalysis Version 1
* 2023: SQAD: Automatic Smartphone Camera Quality Assessment and Benchmarking
Includes: Ignatov, A. Ignatov, A.[Alexander] Ignatov, A.[Andrey]
41 for Ignatov, A.
Ignatov, D.[Dmitry]
* 2020: Controlling information capacity of binary neural network
Ignatov, D.I.[Dmitry I.]
* 2017: Neural Networks Compression for Language Modeling
Ignatyev, A.[Alexander]
* 2023: Ground-Based Microwave Measurements of Mesospheric Ozone Variations over Moscow Region during the Solar Eclipses of 20 March 2015 and 25 October 2022
Ignatyev, S.[Savva]
* 2020: CAD-deform: Deformable Fitting of CAD Models to 3D Scans
* 2021: Adversarial Generation of Continuous Images
* 2023: Sphere-Guided Training of Neural Implicit Surfaces