no code implementations • 5 Apr 2024 • Christos Siargkas, Vasileios Papapanagiotou, Anastasios Delopoulos
We use very low sampling rates for both signal types to reduce battery consumption.
no code implementations • 29 Apr 2023 • Alexandros Papadopoulos, Anastasios Delopoulos
Yet for large scale studies, obtaining even the necessary coarse ground-truth is not trivial, as a complete neurological evaluation is required.
no code implementations • 31 Aug 2022 • Aristotelis Ballas, Vasileios Papapanagiotou, Anastasios Delopoulos, Christos Diou
The PhysioNet 2022 challenge targets automatic detection of murmur from audio recordings of the heart and automatic detection of normal vs. abnormal clinical outcome.
no code implementations • 11 Aug 2022 • Vasileios Papapanagiotou, Anastasia Liapi, Anastasios Delopoulos
Automatic dietary monitoring has progressed significantly during the last years, offering a variety of solutions, both in terms of sensors and algorithms as well as in terms of what aspect or parameters of eating behavior are measured and monitored.
1 code implementation • 8 Sep 2021 • Athanasios Kirmizis, Konstantinos Kyritsis, Anastasios Delopoulos
In particular, leave-one-subject-out (LOSO) experiments reveal an F1-score of 0. 863 for the detection of puffs and an F1-score/Jaccard index equal to 0. 878/0. 604 towards the temporal localization of smoking sessions during the day.
no code implementations • 2 Aug 2021 • Vasileios Papapanagiotou, Stefanos Ganotakis, Anastasios Delopoulos
While automatic tracking and measuring of our physical activity is a well established domain, not only in research but also in commercial products and every-day life-style, automatic measurement of eating behavior is significantly more limited.
1 code implementation • 2 Aug 2021 • Vasileios Papapanagiotou, Christos Diou, Anastasios Delopoulos
A common bottleneck for developing and training machine learning algorithms is obtaining labeled data for training supervised algorithms, and in particular ground truth annotations.
no code implementations • 20 May 2021 • Vasileios Papapanagiotou, Christos Diou, Janet van den Boer, Monica Mars, Anastasios Delopoulos
Our approach performs very well in recognizing crispiness (0. 95 weighted accuracy on new subjects and 0. 93 on new food types) and demonstrates promising results for objective and automatic recognition of wetness and chewiness.
no code implementations • 2 Mar 2021 • Alexandros Papadopoulos, Fotis Topouzis, Anastasios Delopoulos
Diabetic Retinopathy (DR) is a leading cause of vision loss globally.
no code implementations • 12 Oct 2020 • Konstantinos Kyritsis, Christos Diou, Anastasios Delopoulos
The increased worldwide prevalence of obesity has sparked the interest of the scientific community towards tools that objectively and automatically monitor eating behavior.
no code implementations • 6 May 2020 • Alexandros Papadopoulos, Konstantinos Kyritsis, Lisa Klingelhoefer, Sevasti Bostanjopoulou, K. Ray Chaudhuri, Anastasios Delopoulos
Parkinson's Disease (PD) is a slowly evolving neuro-logical disease that affects about 1% of the population above 60 years old, causing symptoms that are subtle at first, but whose intensity increases as the disease progresses.
no code implementations • 17 Sep 2018 • Ioannis Sarafis, Christos Diou, Anastasios Delopoulos
Experiments on 14 benchmark data sets and data sets with importance scores for the training instances show that: (a) the condition for the existence of span in weighted SVM is satisfied almost always; (b) the span-rule is the most effective method for weighted SVM hyperparameter selection; (c) the span-rule is the best predictor of the test error in the mean square error sense; and (d) the span-rule is efficient and, for certain problems, it can be calculated faster than $K$-fold cross-validation.
no code implementations • 26 Jun 2017 • Angelos Katharopoulos, Despoina Paschalidou, Christos Diou, Anastasios Delopoulos
This paper introduces a family of local feature aggregation functions and a novel method to estimate their parameters, such that they generate optimal representations for classification (or any task that can be expressed as a cost function minimization problem).