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Classification of Depressive Episodes Using Nighttime Data; a Multivariate and Univariate Analysis

Programming and computer software, 2020-12, Vol.46 (8), p.689-698

2020

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CAPACITY BUILDING FOR GIS-BASED SDG INDICATORS ANALYSIS WITH GLOBAL HIGH-RESOLUTION LAND COVER DATASETS

International archives of the photogrammetry, remote sensing and spatial information sciences., 2023, Vol.XLVIII-1/W2-2023, p.559-564

2023

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Controlled and Secure Access to Promote the Industrial Internet of Things

IEEE access, 2018-01, Vol.6, p.48289-48299

2018

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An Evolutive Linear Kinematic Source Inversion

Journal of geophysical research. Solid earth, 2018-06, Vol.123 (6), p.4859-4885

2018

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Quality of Service in Software Defined Networks for Scientific Applications: Opportunities and Challenges

Programming and computer software, 2020-12, Vol.46 (8), p.561-568

2020

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No New-Net

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.234-244

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Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.92-104

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3D MRI Brain Tumor Segmentation Using Autoencoder Regularization

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.311-320

Myronenko, Andriy

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Biomedical literature classification with a CNNs-based hybrid learning network

PloS one, 2018-07, Vol.13 (7), p.e0197933-e0197933

2018

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The Effects of an Interactive Software Agent on Student Affective Dynamics while Using ;an Intelligent Tutoring System

IEEE transactions on affective computing, 2012-04, Vol.3 (2), p.224-236

2012

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IEEE_Xplore

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support: Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

1st Edition 2019, 2019

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Construction of a Repeatable Framework for Prostate Cancer Lesion Binary Semantic Segmentation using Convolutional Neural Networks

International journal of advanced computer science & applications, 2022-01, Vol.13 (6)

2022

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Performance Evaluation of Face Mask Detection for Real-Time Implementation on an Rpi

International journal of advanced computer science & applications, 2023, Vol.14 (7)

2023

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Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data: 4th International Workshop, iMIMIC 2021, and 1st International Workshop, TDA4MedicalData 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

1st Edition 2021, 2021

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S3D-UNet: Separable 3D U-Net for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.358-368

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Intrinsic Image Decomposition via Structure-Preserving Image Smoothing and Material Recognition

PloS one, 2016-12, Vol.11 (12), p.e0166772-e0166772

2016

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DeepMedic for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.138-149

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Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.161-169

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Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.456-465

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Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.287-297

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Estimating a Logistic Discrimination Functions When One of the Training Samples Is Subject to Misclassification: A Maximum Likelihood Approach

PloS one, 2015-10, Vol.10 (10), p.e0140718-e0140718

2015

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Automatic Brain Tumor Segmentation Using Cascaded Anisotropic Convolutional Neural Networks

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.178-190

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Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.450-462

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Learning Contextual and Attentive Information for Brain Tumor Segmentation

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, p.497-507

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Deep Neural Network or Dermatologist?

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support, p.48-55

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Classification of Depressive Episodes Using Nighttime Data; a Multivariate and Univariate Analysis

CAPACITY BUILDING FOR GIS-BASED SDG INDICATORS ANALYSIS WITH GLOBAL HIGH-RESOLUTION LAND COVER DATASETS

Controlled and Secure Access to Promote the Industrial Internet of Things

An Evolutive Linear Kinematic Source Inversion

Quality of Service in Software Defined Networks for Scientific Applications: Opportunities and Challenges

No New-Net

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation

3D MRI Brain Tumor Segmentation Using Autoencoder Regularization

Biomedical literature classification with a CNNs-based hybrid learning network

The Effects of an Interactive Software Agent on Student Affective Dynamics while Using ;an Intelligent Tutoring System

Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support: Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

Construction of a Repeatable Framework for Prostate Cancer Lesion Binary Semantic Segmentation using Convolutional Neural Networks

Performance Evaluation of Face Mask Detection for Real-Time Implementation on an Rpi

S3D-UNet: Separable 3D U-Net for Brain Tumor Segmentation

Intrinsic Image Decomposition via Structure-Preserving Image Smoothing and Material Recognition

DeepMedic for Brain Tumor Segmentation

Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images

Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation

Brain Tumor Segmentation and Radiomics Survival Prediction: Contribution to the BRATS 2017 Challenge

Estimating a Logistic Discrimination Functions When One of the Training Samples Is Subject to Misclassification: A Maximum Likelihood Approach

Automatic Brain Tumor Segmentation Using Cascaded Anisotropic Convolutional Neural Networks

Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation

Learning Contextual and Attentive Information for Brain Tumor Segmentation

Deep Neural Network or Dermatologist?

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