Jordina Torrents-Barrena

Orcid: 0000-0002-7380-6297

According to our database1, Jordina Torrents-Barrena authored at least 37 papers between 2014 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
FPGA-Based Accelerator for AI-Toolbox Reinforcement Learning Library.
IEEE Embed. Syst. Lett., June, 2023

Dataset Similarity to Assess Semisupervised Learning Under Distribution Mismatch Between the Labeled and Unlabeled Datasets.
IEEE Trans. Artif. Intell., April, 2023

Invariance measures for neural networks.
Appl. Soft Comput., 2023

2022
FPGA acceleration analysis of LibSVM predictors based on high-level synthesis.
J. Supercomput., 2022

Generalisability of deep learning models in low-resource imaging settings: A fetal ultrasound study in 5 African countries.
CoRR, 2022

2021
A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images.
Expert Syst. Appl., 2021

Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images.
Proceedings of the Advances in Computational Intelligence, 2021

2020
TTTS-STgan: Stacked Generative Adversarial Networks for TTTS Fetal Surgery Planning Based on 3D Ultrasound.
IEEE Trans. Medical Imaging, 2020

Deep Q-CapsNet Reinforcement Learning Framework for Intrauterine Cavity Segmentation in TTTS Fetal Surgery Planning.
IEEE Trans. Medical Imaging, 2020

Breast tumor segmentation and shape classification in mammograms using generative adversarial and convolutional neural network.
Expert Syst. Appl., 2020

MixMOOD: A systematic approach to class distribution mismatch in semi-supervised learning using deep dataset dissimilarity measures.
CoRR, 2020

Convexity shape constraints for retinal blood vessel segmentation and foveal avascular zone detection.
Comput. Biol. Medicine, 2020

Segmentation of the placenta and its vascular tree in Doppler ultrasound for fetal surgery planning.
Int. J. Comput. Assist. Radiol. Surg., 2020

A First Glance to the Quality Assessment of Dental Photostimulable Phosphor Plates with Deep Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Dealing with Scarce Labelled Data: Semi-supervised Deep Learning with Mix Match for Covid-19 Detection Using Chest X-ray Images.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Deep learning -based segmentation methods for computer-assisted fetal surgery.
PhD thesis, 2019

Fully automatic 3D reconstruction of the placenta and its peripheral vasculature in intrauterine fetal MRI.
Medical Image Anal., 2019

Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects.
Medical Image Anal., 2019

TTTS-GPS: Patient-specific preoperative planning and simulation platform for twin-to-twin transfusion syndrome fetal surgery.
Comput. Methods Programs Biomed., 2019

Measuring (in)variances in Convolutional Networks.
Proceedings of the 7th Conference on Cloud Computing & Big Data, 2019

Automatic Segmentation Of the Placenta and its Peripheral Vasculature in Volumetric Ultrasound for TTTS Fetal Surgery.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Unsharp Masking Layer: Injecting Prior Knowledge in Convolutional Networks for Image Classification.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Image Processing, 2019

Assessing the Impact of a Preprocessing Stage on Deep Learning Architectures for Breast Tumor Multi-class Classification with Histopathological Images.
Proceedings of the High Performance Computing - 6th Latin American Conference, 2019

2018
Breast Mass Segmentation and Shape Classification in Mammograms Using Deep Neural Networks.
CoRR, 2018

Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification.
CoRR, 2018

Preoperative Planning and Simulation Framework for Twin-to-Twin Transfusion Syndrome Fetal Surgery.
Proceedings of the OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, - and - Skin Image Analysis, 2018

Conditional Generative Adversarial and Convolutional Networks for X-ray Breast Mass Segmentation and Shape Classification.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Fetal MRI Synthesis via Balanced Auto-Encoder Based Generative Adversarial Networks.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Retinal Optic Disc Segmentation Using Conditional Generative Adversarial Network.
Proceedings of the Artificial Intelligence Research and Development, 2018

2017
Classification of Breast Cancer Molecular Subtypes from Their Micro-Texture in Mammograms Using a VGGNet-Based Convolutional Neural Network.
Proceedings of the Recent Advances in Artificial Intelligence Research and Development, 2017

2016
Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images.
J. Exp. Theor. Artif. Intell., 2016

A novel wavelet seismic denoising method using type II fuzzy.
Appl. Soft Comput., 2016

Interactive Optic Disk Segmentation via Discrete Convexity Shape Knowledge Using High-Order Functionals.
Proceedings of the Artificial Intelligence Research and Development, 2016

2015
Screening for Diabetic Retinopathy through Retinal Colour Fundus Images using Convolutional Neural Networks.
Proceedings of the Artificial Intelligence Research and Development, 2015

Automatic Recognition of Molecular Subtypes of Breast Cancer in X-Ray images using Segmentation-based Fractal Texture Analysis.
Proceedings of the Artificial Intelligence Research and Development, 2015

2014
Breast Masses Identification through Pixel-Based Texture Classification.
Proceedings of the Breast Imaging - 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29, 2014

Analysis of Gabor-Based Texture Features for the Identification of Breast Tumor Regions in Mammograms.
Proceedings of the Artificial Intelligence Research and Development, 2014


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