125 citations · 230 across the 10 of their papers we have counts for
12 papers
Prototype-Rule Neurosymbolic Regularization for Rank-Constrained Tensor Neural Networks under Label Scarcity
Eftychios Protopapadakis, Konstantinos Makantasis, Konstantinos M. Giannoutakis
Rank-constrained tensor neural networks reduce the parameterization of high-order inputs, but they do not explicitly constrain class geometry in the learned representation. This st…
Learning using privileged information for segmenting tumors on digital mammograms
Ioannis N. Tzortzis, Konstantinos Makantasis, Ioannis Rallis +3
Limited amount of data and data sharing restrictions, due to GDPR compliance, constitute two common factors leading to reduced availability and accessibility when referring to medi…
Automatic inspection of cultural monuments using deep and tensor-based learning on hyperspectral imagery
Ioannis N. Tzortzis, Ioannis Rallis, Konstantinos Makantasis +3
In Cultural Heritage, hyperspectral images are commonly used since they provide extended information regarding the optical properties of materials. Thus, the processing of such hig…
Rank-R FNN: A Tensor-Based Learning Model for High-Order Data Classification
Konstantinos Makantasis, Alexandros Georgogiannis, Athanasios Voulodimos +3
An increasing number of emerging applications in data science and engineering are based on multidimensional and structurally rich data. The irregularities, however, of high-dimensi…
Space-Time Domain Tensor Neural Networks: An Application on Human Pose Classification
Konstantinos Makantasis, Athanasios Voulodimos, Anastasios Doulamis +2
Recent advances in sensing technologies require the design and development of pattern recognition models capable of processing spatiotemporal data efficiently. In this study, we pr…
Deep Reinforcement-Learning-based Driving Policy for Autonomous Road Vehicles
Konstantinos Makantasis, Maria Kontorinaki, Ioannis Nikolos
In this work the problem of path planning for an autonomous vehicle that moves on a freeway is considered. The most common approaches that are used to address this problem are base…
A Deep Reinforcement Learning Driving Policy for Autonomous Road Vehicles
Konstantinos Makantasis, Maria Kontorinaki, Ioannis Nikolos
This work regards our preliminary investigation on the problem of path planning for autonomous vehicles that move on a freeway. We approach this problem by proposing a driving poli…
Common Mode Patterns for Supervised Tensor Subspace Learning
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis +1
In this work we propose a method for reducing the dimensionality of tensor objects in a binary classification framework. The proposed Common Mode Patterns method takes into conside…
Tensor-based Nonlinear Classifier for High-Order Data Analysis
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis +2
In this paper we propose a tensor-based nonlinear model for high-order data classification. The advantages of the proposed scheme are that (i) it significantly reduces the number o…
Tensor-Based Classifiers for Hyperspectral Data Analysis
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis +1
In this work, we present tensor-based linear and nonlinear models for hyperspectral data classification and analysis. By exploiting principles of tensor algebra, we introduce new c…
Data-Driven Background Subtraction Algorithm for in-Camera Acceleration in Thermal Imagery
Konstantinos Makantasis, Antonis Nikitakis, Anastasios Doulamis +2
Detection of moving objects in videos is a crucial step towards successful surveillance and monitoring applications. A key component for such tasks is called background subtraction…
Variational Inference for Background Subtraction in Infrared Imagery
Konstantinos Makantasis, Anastasios Doulamis, Nikolaos Doulamis
We propose a Gaussian mixture model for background subtraction in infrared imagery. Following a Bayesian approach, our method automatically estimates the number of Gaussian compone…