Gustavo Carneiro

According to our database1, Gustavo Carneiro authored at least 179 papers between 2002 and 2021.

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Bibliography

2021
LOW: Training deep neural networks by learning optimal sample weights.
Pattern Recognit., 2021

Convolutional Nets Versus Vision Transformers for Diabetic Foot Ulcer Classification.
CoRR, 2021

PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels.
CoRR, 2021

Multi-centred Strong Augmentation via Contrastive Learning for Unsupervised Lesion Detection and Segmentation.
CoRR, 2021

Probabilistic task modelling for meta-learning.
CoRR, 2021

ScanMix: Learning from Severe Label Noise via Semantic Clustering and Semi-Supervised Learning.
CoRR, 2021

LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment.
CoRR, 2021

Noisy Label Learning for Large-scale Medical Image Classification.
CoRR, 2021

Similarity of Classification Tasks.
CoRR, 2021

Unsupervised Anomaly Detection and Localisation with Multi-scale Interpolated Gaussian Descriptors.
CoRR, 2021

Weakly-supervised Video Anomaly Detection with Contrastive Learning of Long and Short-range Temporal Features.
CoRR, 2021

Detecting, Localising and Classifying Polyps from Colonoscopy Videos using Deep Learning.
CoRR, 2021

Artificial intelligence for the diagnosis of lymph node metastases in patients with abdominopelvic malignancy: A systematic review and meta-analysis.
Artif. Intell. Medicine, 2021

EvidentialMix: Learning with Combined Open-set and Closed-set Noisy Labels.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Self-Supervised Lesion Change Detection and Localisation in Longitudinal Multiple Sclerosis Brain Imaging.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Self-supervised Mean Teacher for Semi-supervised Chest X-Ray Classification.
Proceedings of the Machine Learning in Medical Imaging - 12th International Workshop, 2021

3D Semantic Mapping from Arthroscopy Using Out-of-Distribution Pose and Depth and In-Distribution Segmentation Training.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Balanced-MixUp for Highly Imbalanced Medical Image Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Post-Hoc Overall Survival Time Prediction From Brain MRI.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Multi-Center Polyp Segmentation withDouble Encoder-Decoder Networks.
Proceedings of the 3rd International Workshop and Challenge on Computer Vision in Endoscopy (EndoCV 2021) co-located with with the 18th IEEE International Symposium on Biomedical Imaging (ISBI 2021), 2021

Lessons Learned from the Development and Application of Medical Imaging-Based AI Technologies for Combating COVID-19: Why Discuss, What Next.
Proceedings of the Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, 2021

Domain Generalisation with Domain Augmented Supervised Contrastive Learning (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
One Shot Segmentation: Unifying Rigid Detection and Non-Rigid Segmentation Using Elastic Regularization.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Approximate Fisher Information Matrix to Characterize the Training of Deep Neural Networks.
IEEE Trans. Pattern Anal. Mach. Intell., 2020

Siam-U-Net: encoder-decoder siamese network for knee cartilage tracking in ultrasound images.
Medical Image Anal., 2020

Deep learning uncertainty and confidence calibration for the five-class polyp classification from colonoscopy.
Medical Image Anal., 2020

Special Issue on Deep Learning for Robotic Vision.
Int. J. Comput. Vis., 2020

Semantics for Robotic Mapping, Perception and Interaction: A Survey.
Found. Trends Robotics, 2020

PAC-Bayesian Meta-learning with Implicit Prior.
CoRR, 2020

Special issue: 4th MICCAI workshop on deep learning in medical image analysis.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020

Automatic Segmentation of Multiple Structures in Knee Arthroscopy Using Deep Learning.
IEEE Access, 2020

Saliency Improvement in Feature-Poor Surgical Environments Using Local Laplacian of Specified Histograms.
IEEE Access, 2020

Bayesian CNN for Segmentation Uncertainty Inference on 4D Ultrasound Images of the Femoral Cartilage for Guidance in Robotic Knee Arthroscopy.
IEEE Access, 2020

Uncertainty in Model-Agnostic Meta-Learning using Variational Inference.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Probabilistic Object Detection: Definition and Evaluation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2020

Why are Generative Adversarial Networks so Fascinating and Annoying?
Proceedings of the 33rd SIBGRAPI Conference on Graphics, Patterns and Images, 2020

A Survey on Deep Learning with Noisy Labels: How to train your model when you cannot trust on the annotations?
Proceedings of the 33rd SIBGRAPI Conference on Graphics, Patterns and Images, 2020

Few-Shot Microscopy Image Cell Segmentation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Few-Shot Anomaly Detection for Polyp Frames from Colonoscopy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Region Proposals for Saliency Map Refinement for Weakly-Supervised Disease Localisation and Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Unsupervised Task Design to Meta-Train Medical Image Classifiers.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Photoshopping Colonoscopy Video Frames.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Semi-Supervised Multi-Domain Multi-Task Training for Metastatic Colon Lymph Node Diagnosis from Abdominal CT.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

A Hierarchical Multi-task Approach to Gastrointestinal Image Analysis.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation.
Proceedings of the Pattern Recognition. ICPR International Workshops and Challenges, 2020

Creating Classifier Ensembles through Meta-heuristic Algorithms for Aerial Scene Classification.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Generalised Zero-shot Learning with Multi-modal Embedding Spaces.
Proceedings of the Digital Image Computing: Techniques and Applications, 2020

Self-Supervised Monocular Trained Depth Estimation Using Self-Attention and Discrete Disparity Volume.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Hidden stratification causes clinically meaningful failures in machine learning for medical imaging.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

Deep Metric Learning Meets Deep Clustering: An Novel Unsupervised Approach for Feature Embedding.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Augmentation Network for Generalised Zero-Shot Learning.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
Pre and post-hoc diagnosis and interpretation of malignancy from breast DCE-MRI.
Medical Image Anal., 2019

Generalised Zero-Shot Learning with a Classifier Ensemble over Multi-Modal Embedding Spaces.
CoRR, 2019

Few-Shot Meta-Denoising.
CoRR, 2019

Multi-modal Ensemble Classification for Generalized Zero Shot Learning.
CoRR, 2019

Editorial.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2019

One-Stage Five-Class Polyp Detection and Classification.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

End-To-End Diagnosis And Segmentation Learning From Cardiac Magnetic Resonance Imaging.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Model Agnostic Saliency For Weakly Supervised Lesion Detection From Breast DCE-MRI.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Producing Radiologist-Quality Reports for Interpretable Deep Learning.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Bayesian Generative Active Deep Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Single View 3D Point Cloud Reconstruction using Novel View Synthesis and Self-Supervised Depth Estimation.
Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

Generalised Zero-Shot Learning with Domain Classification in a Joint Semantic and Visual Space.
Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, 2019

2018
Probability-based Detection Quality (PDQ): A Probabilistic Approach to Detection Evaluation.
CoRR, 2018

Approximate Fisher Information Matrix to Characterise the Training of Deep Neural Networks.
CoRR, 2018

Producing radiologist-quality reports for interpretable artificial intelligence.
CoRR, 2018

1st MICCAI workshop on deep learning in medical image analysis.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018

Training Medical Image Analysis Systems like Radiologists.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Bayesian Semantic Instance Segmentation in Open Set World.
Proceedings of the Computer Vision - ECCV 2018, 2018

Multi-modal Cycle-Consistent Generalized Zero-Shot Learning.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Fully Automated Segmentation Using Distance Regularised Level Set and Deep-Structured Learning and Inference.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017

Combining Deep Learning and Structured Prediction for Segmenting Masses in Mammograms.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017

Review of Deep Learning Methods in Mammography, Cardiovascular, and Microscopy Image Analysis.
Proceedings of the Deep Learning and Convolutional Neural Networks for Medical Image Computing, 2017

Automatic Quantification of Tumour Hypoxia From Multi-Modal Microscopy Images Using Weakly-Supervised Learning Methods.
IEEE Trans. Medical Imaging, 2017

Automated Analysis of Unregistered Multi-View Mammograms With Deep Learning.
IEEE Trans. Medical Imaging, 2017

Evaluation of Three Algorithms for the Segmentation of Overlapping Cervical Cells.
IEEE J. Biomed. Health Informatics, 2017

Deep Learning on Sparse Manifolds for Faster Object Segmentation.
IEEE Trans. Image Process., 2017

Improving the performance of pedestrian detectors using convolutional learning.
Pattern Recognit., 2017

A deep convolutional neural network module that promotes competition of multiple-size filters.
Pattern Recognit., 2017

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.
Medical Image Anal., 2017

A deep learning approach for the analysis of masses in mammograms with minimal user intervention.
Medical Image Anal., 2017

Detecting hip fractures with radiologist-level performance using deep neural networks.
CoRR, 2017

A Bayesian Data Augmentation Approach for Learning Deep Models.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Globally optimal breast mass segmentation from DCE-MRI using deep semantic segmentation as shape prior.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Fully automated classification of mammograms using deep residual neural networks.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography.
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017

Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017

Scaling CNNs for High Resolution Volumetric Reconstruction from a Single Image.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

Smart Mining for Deep Metric Learning.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Multi-channel Convolutional Neural Network Ensemble for Pedestrian Detection.
Proceedings of the Pattern Recognition and Image Analysis - 8th Iberian Conference, 2017

Region of Interest Autoencoders with an Application to Pedestrian Detection.
Proceedings of the 2017 International Conference on Digital Image Computing: Techniques and Applications, 2017

Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1.
Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017

2016
Automated Detection of Individual Micro-calcifications from Mammograms using a Multi-stage Cascade Approach.
CoRR, 2016

On the importance of normalisation layers in deep learning with piecewise linear activation units.
Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision, 2016

The Automated Learning of Deep Features for Breast Mass Classification from Mammograms.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016

CRISTAL: Adapting Workplace Training to the Real World Context with an Intelligent Simulator for Radiology Trainees.
Proceedings of the Intelligent Tutoring Systems - 13th International Conference, 2016

Multi-atlas segmentation using manifold learning with deep belief networks.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue.
Proceedings of the Computer Vision - ECCV 2016, 2016

Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimizing Global Loss Functions.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
An Improved Joint Optimization of Multiple Level Set Functions for the Segmentation of Overlapping Cervical Cells.
IEEE Trans. Image Process., 2015

Competitive Multi-scale Convolution.
CoRR, 2015

Learning Local Image Descriptors with Deep Siamese and Triplet Convolutional Networks by Minimising Global Loss Functions.
CoRR, 2015

Deep Learning and Structured Prediction for the Segmentation of Mass in Mammograms.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Flexible and Latent Structured Output Learning - Application to Histology.
Proceedings of the Machine Learning in Medical Imaging - 6th International Workshop, 2015

Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference Munich, Germany, October 5, 2015

Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms.
Proceedings of the 12th IEEE International Symposium on Biomedical Imaging, 2015

Lung segmentation in chest radiographs using distance regularized level set and deep-structured learning and inference.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Towards reduction of the training and search running time complexities for non-rigid object segmentation.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

The use of deep learning features in a hierarchical classifier learned with the minimization of a non-greedy loss function that delays gratification.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Deep structured learning for mass segmentation from mammograms.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Automatic detection of necrosis, normoxia and hypoxia in tumors from multimodal cytological images.
Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Weakly-Supervised Structured Output Learning with Flexible and Latent Graphs Using High-Order Loss Functions.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

Robust Optimization for Deep Regression.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

3-D Modeling from Concept Sketches of Human Characters with Minimal User Interaction.
Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

Automated Mass Detection in Mammograms Using Cascaded Deep Learning and Random Forests.
Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

2014
Management driven hybrid multicast framework for content aware networks.
IEEE Commun. Mag., 2014

Artistic Image Analysis Using the Composition of Human Figures.
Proceedings of the Computer Vision - ECCV 2014 Workshops, 2014

Fully Automated Non-rigid Segmentation with Distance Regularized Level Set Evolution Initialized and Constrained by Deep-Structured Inference.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

Non-rigid Segmentation Using Sparse Low Dimensional Manifolds and Deep Belief Networks.
Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014

2013
Artistic Image Analysis Using Graph-Based Learning Approaches.
IEEE Trans. Image Process., 2013

Combining Multiple Dynamic Models and Deep Learning Architectures for Tracking the Left Ventricle Endocardium in Ultrasound Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

Fuzzy clustering based encoding for Visual Object Classification.
Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting, 2013

Left ventricle segmentation from cardiac MRI combining level set methods with deep belief networks.
Proceedings of the IEEE International Conference on Image Processing, 2013

Combining a bottom up and top down classifiers for the segmentation of the left ventricle from cardiac imagery.
Proceedings of the IEEE International Conference on Image Processing, 2013

Point Correspondence Validation under Unknown Radial Distortion.
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013

Closed-Loop Deep Vision.
Proceedings of the 2013 International Conference on Digital Image Computing: Techniques and Applications, 2013

Top-Down Segmentation of Non-rigid Visual Objects Using Derivative-Based Search on Sparse Manifolds.
Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013

2012
The Segmentation of the Left Ventricle of the Heart From Ultrasound Data Using Deep Learning Architectures and Derivative-Based Search Methods.
IEEE Trans. Image Process., 2012

An ns-3 architecture for simulating joint radio resource management strategies in interconnected WLAN and UMTS networks.
Trans. Emerg. Telecommun. Technol., 2012

Transparent and scalable terminal mobility for vehicular networks.
Comput. Networks, 2012

On-line re-training and segmentation with reduction of the training set: Application to the left ventricle detection in ultrasound imaging.
Proceedings of the 19th IEEE International Conference on Image Processing, 2012

In Defence of RANSAC for Outlier Rejection in Deformable Registration.
Proceedings of the Computer Vision - ECCV 2012, 2012

Artistic Image Classification: An Analysis on the PRINTART Database.
Proceedings of the Computer Vision - ECCV 2012, 2012

The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle segmentation in ultrasound.
Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011
Fast prototyping of network protocols through ns-3 simulation model reuse.
Simul. Model. Pract. Theory, 2011

Graph-based methods for the automatic annotation and retrieval of art prints.
Proceedings of the 1st International Conference on Multimedia Retrieval, 2011

Semi-supervised self-trainingmodel for the segmentationof the left ventricle of the heart from ultrasound data.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

Reducing the training set using semi-supervised self-training algorithm for segmenting the left ventricle in ultrasound images.
Proceedings of the 18th IEEE International Conference on Image Processing, 2011

Incremental on-line semi-supervised learning for segmenting the left ventricle of the heart from ultrasound data.
Proceedings of the IEEE International Conference on Computer Vision, 2011

2010
Robust left ventricle segmentation from ultrasound data using deep neural networks and efficient search methods.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010

The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

A Comparative Study on the Use of an Ensemble of Feature Extractors for the Automatic Design of Local Image Descriptors.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Efficient search methods and deep belief networks with particle filtering for non-rigid tracking: Application to lip tracking.
Proceedings of the International Conference on Image Processing, 2010

Multiple dynamic models for tracking the left ventricle of the heart from ultrasound data using particle filters and deep learning architectures.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

The automatic design of feature spaces for local image descriptors using an ensemble of non-linear feature extractors.
Proceedings of the Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, 2010

WiMetroNet A Scalable Wireless Network for Metropolitan Transports.
Proceedings of the Sixth Advanced International Conference on Telecommunications, 2010

2009
Minimum Bayes error features for visual recognition.
Image Vis. Comput., 2009

The quantitative characterization of the distinctiveness and robustness of local image descriptors.
Image Vis. Comput., 2009

FlowMonitor: a network monitoring framework for the network simulator 3 (NS-3).
Proceedings of the 4th International Conference on Performance Evaluation Methodologies and Tools, 2009

Fast and Robust 3-D MRI Brain Structure Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009

2008
Detection and Measurement of Fetal Anatomies from Ultrasound Images using a Constrained Probabilistic Boosting Tree.
IEEE Trans. Medical Imaging, 2008

A Discriminative Model-Constrained Graph Cuts Approach to Fully Automated Pediatric Brain Tumor Segmentation in 3-D MRI.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2008

Semantic-based indexing of fetal anatomies from 3-D ultrasound data using global/semi-local context and sequential sampling.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
QoS abstraction layer in 4G access networks.
Telecommun. Syst., 2007

Flexible Spatial Configuration of Local Image Features.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

Supervised Learning of Semantic Classes for Image Annotation and Retrieval.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

Integration of mobility and qos in 4g scenarios.
Proceedings of the Q2SWinet'07, 2007

Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29, 2007

A probabilistic, hierarchical, and discriminant framework for rapid and accurate detection of deformable anatomic structure.
Proceedings of the IEEE 11th International Conference on Computer Vision, 2007

2006
Sparse Flexible Models of Local Features.
Proceedings of the Computer Vision, 2006

Weakly Supervised Top-down Image Segmentation.
Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006

2005
A database centric view of semantic image annotation and retrieval.
Proceedings of the SIGIR 2005: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2005

Robust header compression in 4G networks with QoS support.
Proceedings of the IEEE 16th International Symposium on Personal, 2005

Formulating Semantic Image Annotation as a Supervised Learning Problem.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

The Distinctiveness, Detectability, and Robustness of Local Image Features.
Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005

Minimum Bayes Error Features for Visual Recognition by Sequential Feature Selection and Extraction.
Proceedings of the Second Canadian Conference on Computer and Robot Vision (CRV 2005), 2005

2004
Cross-layer design in 4G wireless terminals.
IEEE Wirel. Commun., 2004

Pruning Local Feature Correspondences Using Shape Context.
Proceedings of the 17th International Conference on Pattern Recognition, 2004

Flexible Spatial Models for Grouping Local Image Features.
Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2004), with CD-ROM, 27 June, 2004

2003
Multi-scale Phase-based Local Features.
Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2003), 2003

2002
Support of IP QoS over UMTS networks.
Proceedings of the 13th IEEE International Symposium on Personal, 2002

What Is the Role of Independence for Visual Recognition?
Proceedings of the Computer Vision, 2002

Phase-Based Local Features.
Proceedings of the Computer Vision, 2002


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