D. Ravì

发表

Deep Learning for Health Informatics

Guang-Zhong Yang, Fani Deligianni, Charence Wong, 2017, IEEE Journal of Biomedical and Health Informatics.

Resizing Based on Gradient Vector Flow Analysis

G. Farinella, S. Battiato, D. Ravì, 2012 .

An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation

Guang-Zhong Yang, Gustavo Marrero Callicó, Roberto Sarmiento, 2018, Sensors.

Applied Digital Imaging

Giovanni Maria Farinella, Sebastiano Battiato, Alessandro Capra, 2010 .

Towards intraoperative hyperspectral imaging: design considerations for neurosurgical applications

Sebastien Ourselin, Yijing Xie, Tom Vercauteren, 2018, The Hamlyn Symposium on Medical Robotics.

Artificial Intelligence and Robotics pdf

Guang-Zhong Yang, Fani Deligianni, Daniele Ravì, 2017, ArXiv.

Manifold Embedding and Semantic Segmentation for Intraoperative Guidance With Hyperspectral Brain Imaging

Guang-Zhong Yang, Daniele Ravì, Himar Fabelo, 2017, IEEE Transactions on Medical Imaging.

In-Vivo Hyperspectral Human Brain Image Database for Brain Cancer Detection

Guang-Zhong Yang, Roberto Sarmiento, David Carrera, 2019, IEEE Access.

Current Applications and Future Promises of Machine Learning in Diffusion MRI

Daniel C. Alexander, Nooshin Ghavami, Andrada Ianuş, 2019, Computational Diffusion MRI.

Saliency-Based Selection of Gradient Vector Flow Paths for Content Aware Image Resizing

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Puglisi, 2014, IEEE Transactions on Image Processing.

Spatio-spectral classification of hyperspectral images for brain cancer detection during surgical operations

Guang-Zhong Yang, Roberto Sarmiento, Himar Fabelo, 2018, PloS one.

Degenerative adversarial neuroimage nets for brain scan simulations: Application in ageing and dementia

Frederik Barkhof, Stefano B. Blumberg, Daniel C. Alexander, 2019, Medical Image Anal..

Degenerative Adversarial NeuroImage Nets for 3D Simulations: Application in Longitudinal MRI pdf

Stefano B. Blumberg, Daniel C. Alexander, Neil P. Oxtoby, 2019, ArXiv.

Bags of phrases with codebooks alignment for near duplicate image detection

Giovanni Maria Farinella, Sebastiano Battiato, Giuseppe Claudio Guarnera, 2010, MiFor '10.

Semantic segmentation of images exploiting DCT based features and random forest

Giovanni Maria Farinella, Sebastiano Battiato, Mirko Guarnera, 2016, Pattern Recognit..

Real-time food intake classification and energy expenditure estimation on a mobile device

Guang-Zhong Yang, Daniele Ravì, Benny P. L. Lo, 2015, 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Degenerative Adversarial NeuroImage Nets: Generating Images that Mimic Disease Progression pdf

Daniele Ravì, Daniel C. Alexander, Neil Oxtoby, 2019, MICCAI.

Augmenting Dementia Cognitive Assessment With Instruction-Less Eye-Tracking Tests

Daniel C Alexander, Silvia Primativo, Jonathan M Schott, 2020, IEEE Journal of Biomedical and Health Informatics.

Deep learning for human activity recognition: A resource efficient implementation on low-power devices

Guang-Zhong Yang, Charence Wong, Daniele Ravì, 2016, 2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN).

Intra-operative hyperspectral imaging for brain tumour detection and delineation: Current progress on the HELICoid project

Gustavo M. Callico, Samuel Ortega, Himar Fabelo, 2016 .

A Deep Learning Approach to on-Node Sensor Data Analytics for Mobile or Wearable Devices

Guang-Zhong Yang, Charence Wong, Daniele Ravì, 2017, IEEE Journal of Biomedical and Health Informatics.

A Cluster-Based Boosting Strategy for Red Eye Removal

Giovanni Maria Farinella, Mirko Guarnera, Giuseppe Messina, 2013 .

DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification

Daniel C. Alexander, F. Barkhof, D. Ravì, 2023, ArXiv.

Learning from irregularly sampled data for endomicroscopy super-resolution: a comparative study of sparse and dense approaches

T. Vercauteren, D. Ravì, M. Clarkson, 2019, International Journal of Computer Assisted Radiology and Surgery.

Learning from Irregularly Sampled Data with Deep Nadaraya–Watson Kernel Regression Networks (NWNet): Application to Endomicroscopy Image Reconstruction

Tom Vercauteren, Stephen P. Pereira, Agnieszka Barbara Szczotka, 2018 .

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction

Daniele Ravì, Tom Vercauteren, Dzhoshkun Ismail Shakir, 2018, International Journal of Computer Assisted Radiology and Surgery.

On the performances of computer vision algorithms on mobile platforms

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Puglisi, 2012, Electronic Imaging.

Description Key Points Input Layer Hidden Layer 1 Hidden Layer

Guang-Zhong Yang, D. Ravì, Charence Wong, 2016 .

Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy

Daniele Ravì, Tom Vercauteren, Stephen P. Pereira, 2019, Medical Image Anal..

Representing scenes for real-time context classification on mobile devices

Giovanni Maria Farinella, Sebastiano Battiato, Mirko Guarnera, 2015, Pattern Recognit..

Spatial Hierarchy of Textons Distributions for Scene Classification

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Gallo, 2009, MMM.

Scene categorization using bag of Textons on spatial hierarchy

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Gallo, 2008, 2008 15th IEEE International Conference on Image Processing.

Exploiting Textons Distributions on Spatial Hierarchy for Scene Classification

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Gallo, 2010, EURASIP J. Image Video Process..

An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training

Daniel C. Alexander, F. Barkhof, D. Ravì, 2022, ArXiv.

Aligning codebooks for near duplicate image detection

Giovanni Maria Farinella, Sebastiano Battiato, Giovanni Puglisi, 2014, Multimedia Tools and Applications.