Vascon, S.
* 2012: stable graph-based representation for object recognition through high-order matching, A
* 2013: Using Dominant Sets for k-NN Prototype Selection
* 2014: Game-Theoretic Probabilistic Approach for Detecting Conversational Groups, A
* 2016: Context aware nonnegative matrix factorization clustering
* 2016: Detecting conversational groups in images and sequences: A robust game-theoretic approach
* 2018: Characterization of Visual Object Representations in Rat Primary Visual Cortex
* 2018: On Association Graph Techniques for Hypergraph Matching
* 2018: Speaker Clustering Using Dominant Sets
* 2018: Transductive Label Augmentation for Improved Deep Network Learning
* 2019: Hypergraph isomorphism using association hypergraphs
* 2020: Biclustering with dominant sets
* 2020: Group Loss for Deep Metric Learning, The
* 2020: Protein function prediction as a graph-transduction game
* 2020: Two sides of the same coin: Improved ancient coin classification using Graph Transduction Games
* 2021: Encoding Brain Networks Through Geodesic Clustering of Functional Connectivity for Multiple Sclerosis Classification
* 2021: Transductive Visual Verb Sense Disambiguation
* 2022: Relaxation Labeling Meets GANs: Solving Jigsaw Puzzles with Missing Borders
* 2023: Group Loss++: A Deeper Look Into Group Loss for Deep Metric Learning, The
* 2023: Locality-aware subgraphs for inductive link prediction in knowledge graphs
* 2023: Semantic Motif Segmentation of Archaeological Fresco Fragments
Includes: Vascon, S. Vascon, S.[Sebastiano]
20 for Vascon, S.
Vasconcellos, M.A.L.[Marcos A. Leiva]
* 2014: Semi-supervised Puzzle-Based Method for Separating the Venous and Arterial Vascular Networks in Retinal Images, A
Vasconcellos, N.C.M.
* 2009: Use of Coherence Measurements between EEG and EMG on Identification of the Myoclonus Locus
Vasconcelos Raposo, J.
* 2021: Delivering Critical Stimuli for Decision Making in VR Training: Evaluation Study of a Firefighter Training Scenario
Includes: Vasconcelos Raposo, J. Vasconcelos-Raposo, J.
Vasconcelos, B.N.[Barbara Nader]
* 2020: Experiments using deep learning for dermoscopy image analysis
Includes: Vasconcelos, B.N.[Barbara Nader] Vasconcelos, B.N.[Bárbara Nader]
Vasconcelos, C.[Cristina]
* 2015: Unsupervised cosegmentation based on global clustering and saliency
* 2021: Impact of Aliasing on Generalization in Deep Convolutional Networks
* 2022: Proper Reuse of Image Classification Features Improves Object Detection
Vasconcelos, C.N.[Cristina N.]
* 2008: Lloyd's Algorithm on GPU
* 2008: Real-Time Video Processing for Multi-Object Chromatic Tracking
* 2009: Bipartite Graph Matching Computation on GPU
* 2020: Experiments using deep learning for dermoscopy image analysis
* 2023: analysis of ConformalLayers' robustness to corruptions in natural images, An
* 2023: CUF: Continuous Upsampling Filters
Includes: Vasconcelos, C.N.[Cristina N.] Vasconcelos, C.N. Vasconcelos, C.N.[Cristina Nader]
Vasconcelos, F.[Francisco]
* 2012: Minimal Solution for Camera Calibration Using Independent Pairwise Correspondences, A
* 2012: Minimal Solution for the Extrinsic Calibration of a Camera and a Laser-Rangefinder, A
* 2016: Person-following UAVs
* 2016: Similarity Registration Problems for 2D/3D Ultrasound Calibration
* 2017: Refractive Structure-from-Motion Through a Flat Refractive Interface
* 2018: Automatic Camera Calibration Using Multiple Sets of Pairwise Correspondences
* 2020: Refractive Two-View Reconstruction for Underwater 3D Vision
* 2022: MSDESIS: Multitask Stereo Disparity Estimation and Surgical Instrument Segmentation
* 2022: SSIS-Seg: Simulation-Supervised Image Synthesis for Surgical Instrument Segmentation
Includes: Vasconcelos, F.[Francisco] Vasconcelos, F.
9 for Vasconcelos, F.
Vasconcelos, F.F.X.[Francisco F.X.]
* 2020: high-efficiency energy and storage approach for IoT applications of facial recognition, A
Vasconcelos, G.C.
* 2004: Neural Networks vs. Logistic Regression: A Comparative Study on a Large Data Set
* 2008: systematic solution for the NN3 Forecasting Competition problem based on an ensemble of MLP neural networks, A
* 2017: Object recognition under severe occlusions with a hidden Markov model approach
Vasconcelos, I.[Ivan]
* 2021: In-Reservoir Waveform Retrieval for Monitoring at Groningen: Seismic Interferometry with Active and Passive Deep Borehole Data
* 2021: Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation
Vasconcelos, L.[Luiz]
* 2007: new intelligent systems approach to 3D animation in television, A
Vasconcelos, L.O.[Levi O.]
* 2015: Scale Invariant Keypoint Detector Based on Visual and Geometrical Cues, A
* 2017: KVD: Scale invariant keypoints by combining visual and depth data
* 2019: Structured Domain Adaptation for 3D Keypoint Estimation
* 2021: Shape Consistent 2D Keypoint Estimation under Domain Shift
Includes: Vasconcelos, L.O.[Levi O.] Vasconcelos, L.O.
Vasconcelos, M.
* 2004: Scalable discriminant feature selection for image retrieval and recognition
* 2006: Weakly Supervised Top-down Image Segmentation
* 2009: Natural Image Statistics and Low-Complexity Feature Selection
* 2013: Estimating the Above-Ground Biomass in Miombo Savanna Woodlands (Mozambique, East Africa) Using L-Band Synthetic Aperture Radar Data
Includes: Vasconcelos, M. Vasconcelos, M.[Manuela]
Vasconcelos, M.J.[Maria J.]
* 2018: Burned area estimations derived from Landsat ETM+ and OLI data: Comparing Genetic Programming with Maximum Likelihood and Classification and Regression Trees
Vasconcelos, M.J.M.[Maria Joao M.]
* 2014: No-reference Blur Assessment of Dermatological Images Acquired via Mobile Devices
* 2014: Principal Axes-Based Asymmetry Assessment Methodology for Skin Lesion Image Analysis
* 2020: Deep Learning Models for Segmentation of Mobile-acquired Dermatological Images
* 2021: Cervical Cancer Detection and Classification in Cytology Images Using a Hybrid Approach
Includes: Vasconcelos, M.J.M.[Maria Joao M.] Vasconcelos, M.J.M.[Maria Joăo M.]
Vasconcelos, M.J.P.[Maria J. P.]
* 2021: Improving Land Cover Classification Using Genetic Programming for Feature Construction
Vasconcelos, N.
* 1997: Pre and Post-Filtering for Low Bit-Rate Video Coding
* 2006: Image Compression using Object-Based Regions of Interest
* 2015: Generic Promotion of Diffusion-Based Salient Object Detection
* 2020: Explainable Object-Induced Action Decision for Autonomous Vehicles
* 2020: Rethinking Differentiable Search for Mixed-Precision Neural Networks
* 2020: Super Diffusion for Salient Object Detection
Vasconcelos, N.M.[Nuno M.]
* 1900: VALHALLA: Visual multimodal-conditioned generation
* 1995: Spatiotemporal model-based optic flow estimation
* 1996: Frame-free video
* 1997: Bayesian Video Modeling Framework for Shot Segmentation and Content Characterization, A
* 1997: Content-Based Pre-Indexed Video
* 1997: Empirical Bayesian EM Based Motion Segmentation
* 1997: Towards Semantically Meaningful Feature Spaces for the Characterization of Video Content
* 1998: Bayesian Framework for Semantic Content Characterization, A
* 1998: Bayesian modeling of video editing and structure: Semantic features for video summarization and browsing
* 1998: Spatiotemporal Motion Model for Video Summarization, A
* 1999: Probabilistic Retrieval: New Insights and Experimental Results
* 2000: Bayesian relevance feedback for content-based image retrieval
* 2000: Learning Over Multiple Temporal Scales in Image Databases
* 2000: Probabilistic Architecture for Content-based Image Retrieval, A
* 2000: Statistical Models of Video Structure for Content Analysis and Characterization
* 2000: Unifying View of Image Similarity, A
* 2001: Content-based Retrieval from Image Databases: Current Solutions and Future Directions
* 2001: Empirical Bayesian Motion Segmentation
* 2001: Image Indexing with Mixture Hierarchies
* 2001: On the Complexity of Probabilistic Image Retrieval
* 2002: Exploiting group structure to improve retrieval accuracy and speed in image databases
* 2002: What Is the Role of Independence for Visual Recognition?
* 2003: family of information-theoretic algorithms for low-complexity discriminant feature selection in image retrieval, A
* 2003: Feature selection by maximum marginal diversity: Optimality and Implications for Visual Recognition
* 2004: Kullback-Leibler Kernel as a Framework for Discriminant and Localized Representations for Visual Recognition, The
* 2004: Scalable discriminant feature selection for image retrieval and recognition
* 2005: Experimental Comparison of Three Guiding Principles for the Detection Salient Image Locations: Stability, Complexity, and Discrimination, An
* 2005: Formulating Semantic Image Annotation as a Supervised Learning Problem
* 2005: Integrated Learning of Saliency, Complex Features, and Object Detectors from Cluttered Scenes
* 2005: Minimum Bayes Error Features for Visual Recognition by Sequential Feature Selection and Extraction
* 2005: Mixtures of Dynamic Textures
* 2005: Probabilistic Kernels for the Classification of Auto-Regressive Visual Processes
* 2006: Query by Semantic Example
* 2006: Weakly Supervised Top-down Image Segmentation
* 2007: Bottom-up saliency is a discriminant process
* 2007: Classifying Video with Kernel Dynamic Textures
* 2007: Discriminant Interest Points are Stable
* 2007: From Pixels to Semantic Spaces: Advances in Content-Based Image Retrieval
* 2007: High Detection-rate Cascades for Real-Time Object Detection
* 2007: Supervised Learning of Semantic Classes for Image Annotation and Retrieval
* 2008: Background subtraction in highly dynamic scenes
* 2008: Complex discriminant features for object classification
* 2008: Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
* 2008: Privacy preserving crowd monitoring: Counting people without people models or tracking
* 2008: Scene classification with low-dimensional semantic spaces and weak supervision
* 2008: study of query by semantic example, A
* 2008: systematic study of the role of context on image classification, A
* 2009: Bayesian Poisson regression for crowd counting
* 2009: Discriminant Saliency, the Detection of Suspicious Coincidences, and Applications to Visual Recognition
* 2009: Holistic context modeling using semantic co-occurrences
* 2009: Layered Dynamic Textures
* 2009: Minimum Bayes error features for visual recognition
* 2009: Natural Image Statistics and Low-Complexity Feature Selection
* 2009: Saliency-based discriminant tracking
* 2009: Variational layered dynamic textures
* 2010: Anomaly detection in crowded scenes
* 2010: Novel Approach to FRUC Using Discriminant Saliency and Frame Segmentation, A
* 2010: On the design of robust classifiers for computer vision
* 2010: Spatiotemporal Saliency in Dynamic Scenes
* 2011: Adapted Gaussian models for image classification
* 2011: Automatic initialization and tracking using attentional mechanisms
* 2011: Biologically plausible detection of amorphous objects in the wild
* 2011: Cost-Sensitive Boosting
* 2011: Generalized Stauffer-Grimson background subtraction for dynamic scenes
* 2011: TaylorBoost: First and second-order boosting algorithms with explicit margin control
* 2012: Boosting algorithms for simultaneous feature extraction and selection
* 2012: Counting People With Low-Level Features and Bayesian Regression
* 2012: Holistic Context Models for Visual Recognition
* 2012: Learning Optimal Embedded Cascades
* 2012: On the regularization of image semantics by modal expansion
* 2012: Scene Recognition on the Semantic Manifold
* 2013: Biologically Inspired Object Tracking Using Center-Surround Saliency Mechanisms
* 2013: Class-Specific Simplex-Latent Dirichlet Allocation for Image Classification
* 2013: Dynamic Pooling for Complex Event Recognition
* 2013: Latent Dirichlet Allocation Models for Image Classification
* 2013: Recognizing Activities via Bag of Words for Attribute Dynamics
* 2014: Anomaly Detection and Localization in Crowded Scenes
* 2014: Cross-modal domain adaptation for text-based regularization of image semantics in image retrieval systems
* 2014: Geodesic Regression on the Grassmannian
* 2014: Learning Optimal Seeds for Diffusion-Based Salient Object Detection
* 2014: Learning Receptive Fields for Pooling from Tensors of Feature Response
* 2014: On the Role of Correlation and Abstraction in Cross-Modal Multimedia Retrieval
* 2014: Robust Deformable and Occluded Object Tracking With Dynamic Graph
* 2015: Bayesian Model Adaptation for Crowd Counts
* 2015: How many bits does it take for a stimulus to be salient?
* 2015: Learning Complexity-Aware Cascades for Deep Pedestrian Detection
* 2015: Multiple instance learning for soft bags via top instances
* 2015: Scene classification with semantic Fisher vectors
* 2016: Boosted Convolutional Neural Networks
* 2016: Parametric Regression on the Grassmannian
* 2016: Peak-Piloted Deep Network for Facial Expression Recognition
* 2016: Person-following UAVs
* 2016: Semantic Clustering for Robust Fine-Grained Scene Recognition
* 2016: Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection, A
* 2016: VLAD3: Encoding Dynamics of Deep Features for Action Recognition
* 2017: AGA: Attribute-Guided Augmentation
* 2017: Complex Activity Recognition Via Attribute Dynamics
* 2017: Deep Learning with Low Precision by Half-Wave Gaussian Quantization
* 2017: Deep Scene Image Classification with the MFAFVNet
* 2017: Semantically Consistent Regularization for Zero-Shot Recognition
* 2018: Cascade R-CNN: Delving Into High Quality Object Detection
* 2018: Feature Space Transfer for Data Augmentation
* 2018: RESOUND: Towards Action Recognition Without Representation Bias
* 2018: Towards Realistic Predictors
* 2019: Bidirectional Learning for Domain Adaptation of Semantic Segmentation
* 2019: Catastrophic Child's Play: Easy to Perform, Hard to Defend Adversarial Attacks
* 2019: Efficient Multi-Domain Learning by Covariance Normalization
* 2019: NetTailor: Tuning the Architecture, Not Just the Weights
* 2019: PIEs: Pose Invariant Embeddings
* 2019: REPAIR: Removing Representation Bias by Dataset Resampling
* 2019: Towards Universal Object Detection by Domain Attention
* 2020: Background Data Resampling for Outlier-Aware Classification
* 2020: Exploit Clues From Views: Self-Supervised and Regularized Learning for Multiview Object Recognition
* 2020: Few-Shot Open-Set Recognition Using Meta-Learning
* 2020: Learning Complexity-Aware Cascades for Pedestrian Detection
* 2020: SCOUT: Self-Aware Discriminant Counterfactual Explanations
* 2020: Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes
* 2020: Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier
* 2020: Spot: Selective Point Cloud Voting for Better Proposal in Point Cloud Object Detection
* 2021: A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation
* 2021: Audio-Visual Instance Discrimination with Cross-Modal Agreement
* 2021: BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning
* 2021: Cascade R-CNN: High Quality Object Detection and Instance Segmentation
* 2021: Deep Hashing with Hash-Consistent Large Margin Proxy Embeddings
* 2021: Dynamic Transfer for Multi-Source Domain Adaptation
* 2021: GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition
* 2021: Gradient-based Algorithms for Machine Teaching
* 2021: IMAGINE: Image Synthesis by Image-Guided Model Inversion
* 2021: Learning Deep Classifiers Consistent with Fine-Grained Novelty Detection
* 2021: Learning of Visual Relations: The Devil is in the Tails
* 2021: Machine Teaching Framework for Scalable Recognition, A
* 2021: MicroNet: Improving Image Recognition with Extremely Low FLOPs
* 2021: Rethinking and Improving the Robustness of Image Style Transfer
* 2021: Robust Audio-Visual Instance Discrimination
* 2022: Black-Box Test-Time Shape REFINEment for Single View 3D Reconstruction
* 2022: Breadcrumbs: Adversarial Class-Balanced Sampling for Long-Tailed Recognition
* 2022: Calibrating Deep Neural Networks by Pairwise Constraints
* 2022: Class-Incremental Learning with Strong Pre-trained Models
* 2022: CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs
* 2022: Improving Video Model Transfer with Dynamic Representation Learning
* 2022: Omni-DETR: Omni-Supervised Object Detection with Transformers
* 2022: Should All Proposals Be Treated Equally in Object Detection?
* 2022: YORO - Lightweight End to End Visual Grounding
* 2023: ActorsNeRF: Animatable Few-shot Human Rendering with Generalizable NeRFs
* 2023: Dense Network Expansion for Class Incremental Learning
* 2023: Generalized Explanation Framework for Visualization of Deep Learning Model Predictions, A
* 2023: SViTT: Temporal Learning of Sparse Video-Text Transformers
* 2023: Toward Unsupervised Realistic Visual Question Answering
* 2023: Towards Professional Level Crowd Annotation of Expert Domain Data
Includes: Vasconcelos, N.M.[Nuno M.] Vasconcelos, N.M.[Nuno Miguel] Vasconcelos, N.M.
149 for Vasconcelos, N.M.
Vasconcelos, R.[Rodrigo]
* 2020: Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine
Vasconcelos, R.C.S.[Raimundo C. S.]
* 2022: Identification of External Defects on Fruits Using Deep Learning
Vasconcelos, R.M.[Rosa M.]
* 2010: Determination of yarn production characteristics using image processing
Vasconcelos, R.N.[Rodrigo N.]
* 2020: Oil Spill Detection and Mapping: A 50-Year Bibliometric Analysis
Vasconez, F.[Freddy]
* 2022: VIGIA: A Thermal and Visible Imagery System to Track Volcanic Explosions
Includes: Vasconez, F.[Freddy] Vásconez, F.[Freddy]
Vasconez, F.J.[Francisco Javier]
* 2022: Near Real-Time and Free Tool for the Preliminary Mapping of Active Lava Flows during Volcanic Crises: The Case of Hotspot Subaerial Eruptions, A