Jacinto C. Nascimento

发表

Automatic 3-D Segmentation of Endocardial Border of the Left Ventricle From Ultrasound Images

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2015, IEEE Journal of Biomedical and Health Informatics.

Combining a bottom up and top down classifiers for the segmentation of the left ventricle from cardiac imagery

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2013, 2013 IEEE International Conference on Image Processing.

Lip contour tracking using multiple dynamic models on a manifold

Jacinto C. Nascimento, Jorge S. Silva, 2011, 2011 18th IEEE International Conference on Image Processing.

Training Medical Image Analysis Systems like Radiologists pdf

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2018, MICCAI.

Top-Down Segmentation of Non-rigid Visual Objects Using Derivative-Based Search on Sparse Manifolds

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

A Window-Based Classifier for Automatic Video-Based Reidentification

Alexandre Bernardino, Jacinto C. Nascimento, Dario Figueira, 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Tracking objects with generic calibrated sensors: An algorithm based on color and 3D shape features

Pedro U. Lima, Alexandre Bernardino, Jacinto C. Nascimento, 2010, Robotics Auton. Syst..

Improving the performance of pedestrian detectors using convolutional learning

Gustavo Carneiro, Alexandre Bernardino, David Ribeiro, 2017, Pattern Recognit..

On the purity of training and testing data for learning: The case of pedestrian detection

Alexandre Bernardino, Jacinto C. Nascimento, Matteo Taiana, 2015, Neurocomputing.

Robust 3D Active Shape Model for the Segmentation of the Left Ventricle in MRI

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2015, IbPRIA.

Medical Image Noise Reduction Using the Sylvester–Lyapunov Equation

João M. Sanches, Jorge S. Marques, Jacinto C. Nascimento, 2008, IEEE Transactions on Image Processing.

Adaptive snakes using the EM algorithm

Jorge S. Marques, Jacinto C. Nascimento, J. Marques, 2005, IEEE Transactions on Image Processing.

Estimation of cardiac phases in echographic images using multiple models

João M. Sanches, Jorge S. Marques, Jacinto C. Nascimento, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

Reducing the training set using semi-supervised self-training algorithm for segmenting the left ventricle in ultrasound images

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2011, 2011 18th IEEE International Conference on Image Processing.

Activity Recognition Using a Mixture of Vector Fields

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2013, IEEE Transactions on Image Processing.

Trajectory Analysis Using Switched Motion Fields: A Parametric Approach

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2011, IbPRIA.

Person Re-identification based on Human Query on Soft Biometrics using SVM Regression

Alexandre Bernardino, Jacinto C. Nascimento, Athira M. Nambiar, 2016, VISIGRAPP.

A multi-camera video dataset for research on high-definition surveillance

Alexandre Bernardino, Jacinto C. Nascimento, Dario Figueira, 2014 .

Towards reduction of the training and search running time complexities for non-rigid object segmentation

Gustavo Carneiro, Jacinto C. Nascimento, 2015, 2015 IEEE International Conference on Image Processing (ICIP).

Multi-channel Convolutional Neural Network Ensemble for Pedestrian Detection

Gustavo Carneiro, Alexandre Bernardino, David Ribeiro, 2017, IbPRIA.

Fast segmentation of the left ventricle in cardiac MRI using dynamic programming

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2018, Comput. Methods Programs Biomed..

Efficient and robust Pedestrian Detection using Deep Learning for Human-Aware Navigation

David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo, 2016, Robotics Auton. Syst..

Performance evaluation of point matching algorithms for left ventricle motion analysis in MRI

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Context-Aware Person Re-Identification in the Wild Via Fusion of Gait and Anthropometric Features

Ana L. N. Fred, Alexandre Bernardino, Jacinto C. Nascimento, 2017, 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017).

2D Segmentation Using a Robust Active Shape Model With the EM Algorithm

Carlos Santiago, Jorge S. Marques, Jacinto C. Nascimento, 2015, IEEE Transactions on Image Processing.

Unsupervised Task Design to Meta-Train Medical Image Classifiers

Gustavo Carneiro, Gabriel Maicas, Jacinto C. Nascimento, 2019, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Corrections to "Adaptive Snakes Using the EM Algorithm"

Jorge S. Marques, Jacinto C. Nascimento, 2006, IEEE Trans. Image Process..

Vision-based Hand Pose Estimation - A Mixed Bottom-up and Top-down Approach

João Sequeira, Alexandre Bernardino, Jacinto C. Nascimento, 2013, VISAPP.

A new robust active shape model formulation for cardiac MRI segmentation

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Flexible trajectory modeling using a mixture of parametric motion fields for video surveillance

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2011, 2011 18th IEEE International Conference on Image Processing.

Pre and Post-hoc Diagnosis and Interpretation of Malignancy from Breast DCE-MRI

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2018, Medical Image Anal..

LOW: Training deep neural networks by learning optimal sample weights

Gustavo Carneiro, Jacinto C. Nascimento, Michele Sasdelli, 2021, Pattern Recognit..

Improving the Robustness of Parametric Shape Tracking with Switched Multiple Models

Jorge S. Marques, Jacinto C. Nascimento, J. Marques, 2001, PRIS.

Deep Learning on Sparse Manifolds for Faster Object Segmentation

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2017, IEEE Transactions on Image Processing.

Segmentation of the left ventricle in cardiac MRI using a probabilistic data association active shape model

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Semi-Supervised Learning of Switched Dynamical Models for Classification of Human Activities in Surveillance Applications

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2007, 2007 IEEE International Conference on Image Processing.

Sample-Based 3D Tracking of Colored Objects : A Flexible Architecture

Alexandre Bernardino, Jacinto C. Nascimento, José António Gaspar, 2008, BMVC.

Unregistered Multiview Mammogram Analysis with Pre-trained Deep Learning Models

Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, 2015, MICCAI.

MOTION SEGMENTATION FOR ACTIVITY SURVEILLANCE

Jorge S. Marques, Jacinto C. Nascimento, A. T. Figueiredo, 2005 .

Performance evaluation of object detection algorithms for video surveillance

Jorge S. Marques, Jacinto C. Nascimento, J. Marques, 2006, IEEE Transactions on Multimedia.

Incremental on-line semi-supervised learning for segmenting the left ventricle of the heart from ultrasound data

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2011, 2011 International Conference on Computer Vision.

A sparse approach to pedestrian trajectory modeling using multiple motion fields

Jorge S. Marques, Jacinto C. Nascimento, Catarina Barata, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Robust Shape Estimation with Deformable Models

Jorge S. Marques, Jacinto C. Nascimento, Arnaldo J. Abrantes, 2009 .

Improving the robustness of gradient vector flowin cluttered images

Jorge S. Marques, Jacinto C. Nascimento, 2010, 2010 IEEE International Conference on Image Processing.

3DRegNet: A Deep Neural Network for 3D Point Registration

Rama Chellappa, Jacinto C. Nascimento, Pedro Miraldo, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Manifold Learning for Object Tracking With Multiple Nonlinear Models

Jorge S. Marques, Jacinto C. Nascimento, Jorge G. Silva, 2014, IEEE Transactions on Image Processing.

Level set segmentation with outlier rejection

Jorge S. Marques, Jacinto C. Nascimento, Margarida Silveira, 2008, 2008 15th IEEE International Conference on Image Processing.

Automated 5-year mortality prediction using deep learning and radiomics features from chest computed tomography

Gustavo Carneiro, Lyle J. Palmer, Andrew P. Bradley, 2016, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Efficient Optimization Algorithm for Space-Variant Mixture of Vector Fields

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2013, IbPRIA.

Unsupervised learning of motion patterns using generative models

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2008, 2008 15th IEEE International Conference on Image Processing.

Learning switching dynamic models for objects tracking

Gilles Celeux, Jorge S. Marques, Jacinto C. Nascimento, 2004, Pattern Recognit..

Trajectory Classification Using Switched Dynamical Hidden Markov Models

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2010, IEEE Transactions on Image Processing.

Information Geometric Algorithm for Estimating Switching Probabilities in Space-Varying HMM

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2014, IEEE Transactions on Image Processing.

Multiple dynamic models for tracking the left ventricle of the heart from ultrasound data using particle filters and deep learning architectures

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Robust shape tracking in the presence of cluttered background

Jorge S. Marques, Jacinto C. Nascimento, 2004, IEEE Trans. Multim..

Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions1

Gustavo Carneiro, Andrew P. Bradley, Jacinto C. Nascimento, 2017, Deep Learning for Medical Image Analysis.

Manifold Learning for Object Tracking with Multiple Motion Dynamics

Jacinto C. Nascimento, Jorge G. Silva, 2010, ECCV.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Gustavo Carneiro, Jaime S. Cardoso, M. Jorge Cardoso, 2017, Lecture Notes in Computer Science.

Person Re-identification in Frontal Gait Sequences via Histogram of Optic Flow Energy Image

Alexandre Bernardino, José Santos-Victor, Jacinto C. Nascimento, 2016, ACIVS.

On-line re-training and segmentation with reduction of the training set: Application to the left ventricle detection in ultrasound imaging

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2012, 2012 19th IEEE International Conference on Image Processing.

Discriminative model selection using a modified Bayesian criterion: Application to trajectory modeling

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2011, 2011 18th IEEE International Conference on Image Processing.

Combining Multiple Dynamic Models and Deep Learning Architectures for Tracking the Left Ventricle Endocardium in Ultrasound Data

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Semi-supervised self-trainingmodel for the segmentationof the left ventricle of the heart from ultrasound data

Gustavo Carneiro, Jacinto C. Nascimento, António Freitas, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Modeling and Classifying Human Activities From Trajectories Using a Class of Space-Varying Parametric Motion Fields

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2013, IEEE Transactions on Image Processing.

1st MICCAI workshop on deep learning in medical image analysis

Gustavo Carneiro, Jaime S. Cardoso, Zhi Lu, 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Robust Deformable Models for 2D and 3D Shape Estimation

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2013 .

The Detection and Segmentation of the Left Ventricle of the Heart from Ultrasound Data using Deep Learning Architectures and Efficient Search Methods

Gustavo Carneiro, Jacinto C. Nascimento, Antonio Freitas, 2011 .

The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle segmentation in ultrasound

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Independent increment processes for human motion recognition

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2008, Comput. Vis. Image Underst..

Towards Touch-Based Medical Image Diagnosis Annotation

Jacinto C. Nascimento, Alfredo Ferreira, Daniel Gonçalves, 2017, ISS.

A Real-Time Pedestrian Detector using Deep Learning for Human-Aware Navigation pdf

David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo, 2016, ArXiv.

Non-rigid Object Segmentation Using Robust Active Shape Models

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2014, AMDO.

3D left ventricular segmentation in echocardiography using a probabilistic data association deformable model

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2013, 2013 IEEE International Conference on Image Processing.

The HDA+ Data Set for Research on Fully Automated Re-identification Systems

Alexandre Bernardino, Jacinto C. Nascimento, Dario Figueira, 2014, ECCV Workshops.

Fast and accurate segmentation of the LV in MR volumes using a deformable model with dynamic programming

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2017, 2017 IEEE International Conference on Image Processing (ICIP).

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

Gustavo Carneiro, João Paulo Papa, Lena Maier-Hein, 2018, DLMIA/ML-CDS@MICCAI.

Robust Deformable Model for Segmenting the Left Ventricle in 3D Volumes of Ultrasound Data

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2012, ICPRAM.

Discriminative model selection for object motion recognition

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2010, 2010 IEEE International Conference on Image Processing.

Sparse motion fields for trajectory prediction

João M. Lemos, Jacinto C. Nascimento, Catarina Barata, 2021, Pattern Recognit..

Combining an Active Shape and Motion Models for Object Segmentation in Image Sequences

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).

A robust active shape model using an expectation-maximization framework

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

On the use of perspective catadioptric sensors for 3D model-based tracking with particle filters

Pedro U. Lima, Alexandre Bernardino, Jacinto C. Nascimento, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Automatic Estimation of Multiple Motion Fields using Object Trajectories and Optical Flow

Jorge S. Marques, Jacinto C. Nascimento, Manya V. Afonso, 2012, ICPRAM.

Tracking the Left Ventricle in Ultrasound Images Based on Total Variation Denoising

João M. Sanches, Jorge S. Marques, Jacinto C. Nascimento, 2007, IbPRIA.

An algorithm for centroid-based tracking of moving objects

Jorge S. Marques, Jacinto C. Nascimento, Arnaldo J. Abrantes, 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

Trajectory Modeling Using Mixtures of Vector Fields

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2009, IbPRIA.

Improved Gradient Vector Flow for robust shape estimation in medical imaging

Jorge S. Marques, Jacinto C. Nascimento, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

A class of space-varying parametric motion fields for human activity recognition

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2012, 2012 19th IEEE International Conference on Image Processing.

Non-rigid Segmentation Using Sparse Low Dimensional Manifolds and Deep Belief Networks

Gustavo Carneiro, Jacinto C. Nascimento, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Shape Context for soft biometrics in person re-identification and database retrieval

Alexandre Bernardino, Jacinto C. Nascimento, Athira M. Nambiar, 2015, Pattern Recognit. Lett..

Towards fully automated person re-identification

Alexandre Bernardino, Jacinto C. Nascimento, Dario Figueira, 2014, 2014 International Conference on Computer Vision Theory and Applications (VISAPP).

OmniDRL: Robust Pedestrian Detection using Deep Reinforcement Learning on Omnidirectional Cameras*

Jacinto C. Nascimento, Pedro Miraldo, Tiago J. Dias, 2019, 2019 International Conference on Robotics and Automation (ICRA).

Gait-based Person Re-identification

Alexandre Bernardino, Jacinto C. Nascimento, Athira Nambiar, 2019, ACM Comput. Surv..

Cross-context Analysis for Long-term View-point Invariant Person Re-identification via Soft-biometrics using Depth Sensor

Alexandre Bernardino, Jacinto C. Nascimento, Athira M. Nambiar, 2018, VISIGRAPP.

Deep Reinforcement Learning for Active Breast Lesion Detection from DCE-MRI

Gustavo Carneiro, Ian D. Reid, Andrew P. Bradley, 2017, MICCAI.

3D Tracking by Catadioptric Vision Based on Particle Filters

Pedro U. Lima, Alexandre Bernardino, Jacinto C. Nascimento, 2008, RoboCup.

A Robust Deformable Model for 3D Segmentation of the Left Ventricle from Ultrasound Data

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2013 .

Multi-atlas segmentation using manifold learning with deep belief networks

Gustavo Carneiro, Jacinto C. Nascimento, G. Carneiro, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Automatic Estimation of Multiple Motion Fields From Video Sequences Using a Region Matching Based Approach

Jorge S. Marques, Jacinto C. Nascimento, Manya V. Afonso, 2014, IEEE Transactions on Multimedia.

Towards View-point Invariant Person Re-identification via Fusion of Anthropometric and Gait Features from Kinect Measurements

Ana L. N. Fred, Alexandre Bernardino, Jacinto C. Nascimento, 2017, VISIGRAPP.

Predictive multiple motion fields for trajectory completion: Application to surveillance systems

Jacinto C. Nascimento, Manya V. Afonso, 2015, 2015 IEEE International Conference on Image Processing (ICIP).

The Segmentation of the Left Ventricle of the Heart From Ultrasound Data Using Deep Learning Architectures and Derivative-Based Search Methods

Gustavo Carneiro, Jacinto C. Nascimento, António Freitas, 2012, IEEE Transactions on Image Processing.

Robust left ventricle segmentation from ultrasound data using deep neural networks and efficient search methods

Gustavo Carneiro, Jacinto C. Nascimento, António Freitas, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

On-Line Classification of Human Activities

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2007, IbPRIA.

An Adaptive Potential for Robust Shape Estimation

Jorge S. Marques, Jacinto C. Nascimento, 2001, BMVC.

Robust shape tracking in the presence of cluttered background

Jorge S. Marques, Jacinto C. Nascimento, J. Marques, 2000, IEEE Transactions on Multimedia.

Robust Shape Tracking With Multiple Models in Ultrasound Images

Jorge S. Marques, Jacinto C. Nascimento, J. Marques, 2008, IEEE Transactions on Image Processing.

Trajectory analysis in natural images using mixtures of vector fields

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

Robust Feature Descriptors for Object Segmentation Using Active Shape Models

Carlos Santiago, Jacinto C. Nascimento, Daniela O. Medley, 2018, ACIVS.

Editorial

Gustavo Carneiro, Jaime S. Cardoso, Zhi Lu, 1875, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI

Ian D. Reid, Gabriel Maicas, Gustavo Carneiro, 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.

Multiple Agents Representation Using Motion Fields

Jorge S. Marques, Jacinto C. Nascimento, Catarina Barata, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Using middle level features for robust shape tracking

Jorge S. Marques, Jacinto C. Nascimento, Arnaldo J. Abrantes, 2003, Pattern Recognit. Lett..

Region Proposals for Saliency Map Refinement for Weakly-supervised Disease Localisation and Classification

Gustavo Carneiro, Gabriel Maicas, Jacinto C. Nascimento, 2020, MICCAI.

Single Camera Hand Pose Estimation from Bottom-Up and Top-Down Processes

João Sequeira, Alexandre Bernardino, Jacinto C. Nascimento, 2013, VISIGRAPP.

A real-time Deep Learning pedestrian detector for robot navigation

David Ribeiro, Jacinto C. Nascimento, Pedro Miraldo, 2017, 2017 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC).

Improving a Switched Vector Field Model for Pedestrian Motion Analysis

Jorge S. Marques, Jacinto C. Nascimento, Catarina Barata, 2018, ACIVS.

Special issue: 4th MICCAI workshop on deep learning in medical image analysis

Gustavo Carneiro, Zhi Lu, João Paulo Papa, 2020, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Recognition of human activities using space dependent switched dynamical models

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2005, IEEE International Conference on Image Processing 2005.

An Improved Labelling for the INRIA Person Data Set for Pedestrian Detection

Alexandre Bernardino, Jacinto C. Nascimento, Matteo Taiana, 2013, IbPRIA.

Efficient search methods and deep belief networks with particle filtering for non-rigid tracking: Application to lip tracking

Gustavo Carneiro, Jacinto C. Nascimento, 2010, 2010 IEEE International Conference on Image Processing.

Deep Learning and Data Labeling for Medical Applications

Jaime S. Cardoso, João Paulo Papa, Julien Cornebise, 2016, Lecture Notes in Computer Science.

Segmenting The Left Ventricle In Cardiac In Cardiac MRI: From Handcrafted To Deep Region Based Descriptors

Jacinto C. Nascimento, Daniela O. Medley, Carlos Santiago, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework

Lyle J. Palmer, Andrew P. Bradley, Jacinto C. Nascimento, 2017, Scientific Reports.

Comparison of Segmentation Methods for Melanoma Diagnosis in Dermoscopy Images

Junji Maeda, Jorge S. Marques, Jacinto C. Nascimento, 2009, IEEE Journal of Selected Topics in Signal Processing.

A new ASM framework for left ventricle segmentation exploring slice variability in cardiac MRI volumes

Jorge S. Marques, Carlos Santiago, Jacinto C. Nascimento, 2017, Neural Computing and Applications.

Classification of complex pedestrian activities from trajectories

Mário A. T. Figueiredo, Jorge S. Marques, Jacinto C. Nascimento, 2010, 2010 IEEE International Conference on Image Processing.

An adaptive potential for robust shape estimation

Jorge S. Marques, Jacinto C. Nascimento, 2003, Image Vis. Comput..

Ultrasound imaging LV tracking with adaptive window size and automatic hyper-parameter estimation

João M. Sanches, Jacinto C. Nascimento, 2008, 2008 15th IEEE International Conference on Image Processing.

Post-Hoc Overall Survival Time Prediction From Brain MRI

Gustavo Carneiro, Gabriel Maicas, Jacinto C. Nascimento, 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Introduction of human-centric AI assistant to aid radiologists for multimodal breast image classification

Carlos Santiago, Jacinto C. Nascimento, Francisco Maria Calisto, 2021, Int. J. Hum. Comput. Stud..

An information geometric framework for the optimization on a discrete probability spaces: Application to human trajectory classification

Jorge S. Marques, Jacinto C. Nascimento, João Miranda Lemos, 2015, Neurocomputing.

The Fusion of Deep Learning Architectures and Particle Filtering Applied to Lip Tracking

Gustavo Carneiro, Jacinto C. Nascimento, 2010, 2010 20th International Conference on Pattern Recognition.