Zanuncio, J.C.[Jose Cola]
* 2019: Remote Sensing to Detect Nests of the Leaf-Cutting Ant Atta sexdens (Hymenoptera: Formicidae) in Teak Plantations
Includes: Zanuncio, J.C.[Jose Cola] Zanuncio, J.C.[José Cola]
Zanutta, A.[Antonio]
* 2018: New Geodetic and Gravimetric Maps to Infer Geodynamics of Antarctica with Insights on Victoria Land
* 2019: Multi-Temporal Investigation of the Boulder Clay Glacier and Northern Foothills (Victoria Land, Antarctica) by Integrated Surveying Techniques
* 2021: Victoria Land, Antarctica: An Improved Geodynamic Interpretation Based on the Strain Rate Field of the Current Crustal Motion and Moho Depth Model
* 2023: Sea Tide Influence on Ice Flow of David Drygalski's Ice Tongue Inferred from Geodetic GNSS Observations and SAR Offset Tracking Analysis
Zanuttigh, P.[Pietro]
* 2005: Greedy Non-Linear Approximation of the Plenoptic Function for Interactive Transmission of 3D Scenes
* 2006: Distortion-Sensitive Synthesis of Texture and Geometry in Interactive 3D Visualization
* 2006: novel framework for the interactive transmission of 3D scenes, A
* 2007: Rate Distortion Framework for 3D Browsing, A
* 2009: Compression of depth information for 3D rendering
* 2010: joint multi-view plus depth image coding scheme based on 3D-warping, A
* 2010: novel multi-view image coding scheme based on view-warping and 3D-DCT, A
* 2010: Probabilistic Approach to ToF and Stereo Data Fusion, A
* 2011: Scene Segmentation Assisted by Stereo Vision
* 2012: Locally Consistent ToF and Stereo Data Fusion
* 2012: Pairwise similarities for scene segmentation combining color and depth data
* 2012: Time-of-Flight Cameras and Microsoft Kinect™
* 2013: 3D Imaging Techniques and Multimedia Applications: Guest editor's introduction
* 2013: Combining color and shape descriptors for 3D model retrieval
* 2013: Scalable Coding of Depth Maps With R-D Optimized Embedding
* 2014: Combining multiple depth-based descriptors for hand gesture recognition
* 2014: Hand gesture recognition with leap motion and kinect devices
* 2014: Scene segmentation from depth and color data driven by surface fitting
* 2015: Probabilistic ToF and Stereo Data Fusion Based on Mixed Pixels Measurement Models
* 2016: Depth map coding with elastic contours and 3D surface prediction
* 2016: Reliable Fusion of ToF and Stereo Depth Driven by Confidence Measures
* 2016: Scene Segmentation Driven by Deep Learning and Surface Fitting
* 2017: Deep learning for 3D shape classification from multiple depth maps
* 2017: Deep Learning for Confidence Information in Stereo and ToF Data Fusion
* 2017: Segmentation and semantic labelling of RGBD data with convolutional neural networks and surface fitting
* 2018: Combination of Spatially-Modulated ToF and Structured Light for MPI-Free Depth Estimation
* 2018: Deep Learning for Multi-path Error Removal in ToF Sensors
* 2018: Joint segmentation of color and depth data based on splitting and merging driven by surface fitting
* 2019: Incremental Learning Techniques for Semantic Segmentation
* 2019: Unsupervised Domain Adaptation for ToF Data Denoising With Adversarial Learning
* 2020: Gmnet: Graph Matching Network for Large Scale Part Semantic Segmentation in the Wild
* 2020: Unsupervised domain adaptation for mobile semantic segmentation based on cycle consistency and feature alignment
* 2021: Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
* 2021: Knowledge distillation for incremental learning in semantic segmentation
* 2021: Latent Space Regularization for Unsupervised Domain Adaptation in Semantic Segmentation
* 2021: RECALL: Replay-based Continual Learning in Semantic Segmentation
* 2021: Semi-supervised Deep Learning Techniques for Spectrum Reconstruction
* 2021: Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings
* 2021: Unsupervised Domain Adaptation with Multiple Domain Discriminators and Adaptive Self-Training
* 2022: Continual coarse-to-fine domain adaptation in semantic segmentation
* 2022: Edge-Aware Graph Matching Network for Part-Based Semantic Segmentation
* 2022: Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Maps, A
* 2022: Unsupervised Domain Adaptation of Deep Networks for ToF Depth Refinement
* 2023: Asynchronous Federated Continual Learning
* 2023: Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning
* 2023: SELMA: SEmantic Large-Scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints
* 2023: SynDrone: Multi-modal UAV Dataset for Urban Scenarios
* 2024: Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers
Includes: Zanuttigh, P.[Pietro] Zanuttigh, P.
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