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20162024
most citedMulti-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis

297 citations · 592 across the 17 of their papers we have counts for

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11 papers · 1 filter

cs.CV2024

A SAM based Tool for Semi-Automatic Food Annotation

Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato +1

The advancement of artificial intelligence (AI) in food and nutrition research is hindered by a critical bottleneck: the lack of annotated food data. Despite the rise of highly eff…

cs.CV2023

No Data Augmentation? Alternative Regularizations for Effective Training on Small Datasets

Lorenzo Brigato, Stavroula Mougiakakou

Solving image classification tasks given small training datasets remains an open challenge for modern computer vision. Aggressive data augmentation and generative models are among…

cs.CV2023★ 5 cited

Food Recognition and Nutritional Apps

Lubnaa Abdur Rahman, Ioannis Papathanail, Lorenzo Brigato +2

Food recognition and nutritional apps are trending technologies that may revolutionise the way people with diabetes manage their diet. Such apps can monitor food intake as a digita…

cs.CV2020★ 2 cited

Partially Supervised Multi-Task Network for Single-View Dietary Assessment

Ya Lu, Thomai Stathopoulou, Stavroula Mougiakakou

Food volume estimation is an essential step in the pipeline of dietary assessment and demands the precise depth estimation of the food surface and table plane. Existing methods bas…

cs.CV2020★ 1 cited

An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients

Ya Lu, Thomai Stathopoulou, Maria F. Vasiloglou +3

Regular monitoring of nutrient intake in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition. Although several methods to estimate nutr…

cs.CV2019★ 3 cited

An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients

Ya Lu, Thomai Stathopoulou, Maria F. Vasiloglou +6

Regular nutrient intake monitoring in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition (DRM). Although several methods to estimate n…

cs.CV2018★ 6 cited

Linear and Deformable Image Registration with 3D Convolutional Neural Networks

Stergios Christodoulidis, Mihir Sahasrabudhe, Maria Vakalopoulou +4

Image registration and in particular deformable registration methods are pillars of medical imaging. Inspired by the recent advances in deep learning, we propose in this paper, a n…

cs.CV2018

A Multi-Task Learning Approach for Meal Assessment

Ya Lu, Dario Allegra, Marios Anthimopoulos +3

Key role in the prevention of diet-related chronic diseases plays the balanced nutrition together with a proper diet. The conventional dietary assessment methods are time-consuming…

cs.CV2018★ 153 cited

Semantic Segmentation of Pathological Lung Tissue with Dilated Fully Convolutional Networks

Marios Anthimopoulos, Stergios Christodoulidis, Lukas Ebner +3

Early and accurate diagnosis of interstitial lung diseases (ILDs) is crucial for making treatment decisions, but can be challenging even for experienced radiologists. The diagnosti…

cs.CV2017

Two-view 3D Reconstruction for Food Volume Estimation

Joachim Dehais, Marios Anthimopoulos, Sergey Shevchik +1

The increasing prevalence of diet-related chronic diseases coupled with the ineffectiveness of traditional diet management methods have resulted in a need for novel tools to accura…

cs.CV2016★ 297 cited

Multi-source Transfer Learning with Convolutional Neural Networks for Lung Pattern Analysis

Stergios Christodoulidis, Marios Anthimopoulos, Lukas Ebner +2

Early diagnosis of interstitial lung diseases is crucial for their treatment, but even experienced physicians find it difficult, as their clinical manifestations are similar. In or…