Papers by Dimitrios Amanatidis
In the current setting of the COVID-19 pandemic people frequently find social media as a convenie... more In the current setting of the COVID-19 pandemic people frequently find social media as a convenient way to express their opinions and concerns as well as either approve or criticize the ongoing reality (τεκτενόμενα). The article tries to investigate the role of the language (greek Vs english) of the Twitter hastags in the dissemination of the information during COVID-19, in Greece. With the use of Node Excel we have extracted official hashtags related to corona virus pandemic in greek(lish) and english, (#menoumespiti #menoumeasfaleis and covid19greece) and we compare the use of them. We proceeded with the construction of the semantic network using textual analysis, in order to reveal the relationships between ideas embedded in text. Visualization of the network reveals the centrality or clustering of certain ideas. This framework of study can prove very useful in opinion mining in social media users' opinion mining.
Cellular neural network (CNN) implementations used in real time image processing are rapidly gene... more Cellular neural network (CNN) implementations used in real time image processing are rapidly generated by a formal High-level synthesis (HLS) toolset in this work. Industrial and academic hardware design projects can benefit from the use of the Custom Coprocessors Compilation (CCC) HLS behavioral synthesise, via the massive reduction in design and verification time. The CCC tool is built with formal compiler-compiler, Logic Programming and XML validation techniques, thus the generated RTL VHDL or Verilog models are provably-correct. In this work, we rapidly modeled CNNs in the ADA programming language, compiled and verified along with all the necessary testbenches in GNU ADA. Edge-detection, halftoning and morphological processing applications were prototyped, so as to evaluate the CCC HLS method, which was the main contribution of this work. The combination of Logic Programming and RDF validation techniques, as well as prototyping of CNN applications made this work unique.
Using behavioural synthesis for hardware generation of a contour-based image segmentation algorithm
2015 International Conference on Information and Digital Technologies, 2015
In this paper, an existing method for detection of geometric active contours is discussed. The me... more In this paper, an existing method for detection of geometric active contours is discussed. The method examines functionals that depend on the curve geometry and image properties in a level-set framework. More specifically, the cost function that is sought to be minimized is formulated as a weighted sum of three integral measures; a robust alignment term that leads the evolving surface to the edges of the desired object, a minimal variance term that measures the homogeneity inside and outside the object, and a geodesic active surface term that is used mainly for regularization. The algorithm is implemented in MatLab, ADA and subsequently, it was ported to a behavioral synthesis tool, the CCC HLS framework in order to deliver correct-by-construction RTL VHDL implementations of computation-intensive applications. This way, behavioral ADA specifications are transformed into RTL micro-architectures which then can be easily implemented by commercial RTL synthesizers. The designs were verified rapidly at the MatLab and compiled ADA code level, as well as RTL-level simulations were executed to prove the argument of the correctness at the level of the automatically generated RTL VHDL implementations.
An integrated, formal high-Level synthesis (HLS) framework is used in this work for hardware impl... more An integrated, formal high-Level synthesis (HLS) framework is used in this work for hardware implementation of cellular neural networks, which are used in real time image processing. The Custom Coprocessors Compilation (CCC) HLS behavioral synthesiser generates correct-by-construction register transferlevel (RTL) VHDL hardware models of computation-intensive applications. Thus, time-consuming RTL and gate-level simulations are avoided and verification time is cut down to a fraction of the usual time that takes to achieve the same goal with traditional approaches. Such applications include image processing with cellular neural networks (CNNs). The synthesizer utilizes formal compiler-compiler and logic programming techniques, to transform algorithmic ADA into RTL VHDL or Verilog which are directly implementable into hardware using any available RTL synthesizer. The CNNs were rapidly coded, compiled and verified along with all the necessary testbenches in GNU ADA. The applications targeted here are edge-detection, halftoning and morphological processing, which are used to evaluate the CCC HLS framework. The contribution of this work is hardware implementation of CNNs using the CCC HLS tools to formally, and rapidly develop, verify and prototype advanced image processing applications.
2011 15th Panhellenic Conference on Informatics, 2011
In this contribution, behavioral synthesis tools are used for hardware implementation of a cellul... more In this contribution, behavioral synthesis tools are used for hardware implementation of a cellular neural network with the ability to accomplish image processing tasks in real time. Behavioral synthesis tools such as the CCC HLS framework can deliver correct-by-construction RTL VHDL implementations of computation-intensive applications such as image processing and cellular neural networks. The tool applies formal techniques to transform behavioral ADA specifications into RTL micro-architectures which then can be easily implemented by commercial RTL synthesizers. Example applications such as, edge-detection, halftoning and morphological operations, validate the presented contribution.
In this contribution, we propose the use of Cellular Neural Networks as an application for the im... more In this contribution, we propose the use of Cellular Neural Networks as an application for the image segmentation of cinematographic image sequences. The proposed approach is based on a Cellular Neural network cost function that takes into account motion and colour. Cellular Neural Networks are of particular interest for hardware implementation due to the inherent parallelism and initial results using an FPGA simulator are also presented.
Neurocomputing, 2004
Segmentation of independently moving foreground elements from background, is a very common proced... more Segmentation of independently moving foreground elements from background, is a very common procedure in digital postproduction. The conventional technique, known as rotoscoping, is carried out manually and is therefore too reliant on human e ort. The industry is interested in an automated method that can correctly locate the boundary and be robust given rapid motion and non-static backgrounds. A cellular neural network is presented that labels pixels by estimated motion, colour, neighbouring and previous labels. The method is accurate, labour-saving and many times faster than manual rotoscoping. Moreover, due to the inherent parallelism and the local nature of the network, the whole process can be implemented on hardware boosting up performance.
Cellular neural network (CNN) implementations used in real time image processing are rapidly gene... more Cellular neural network (CNN) implementations used in real time image processing are rapidly generated by a formal High-level synthesis (HLS) toolset in this work. Industrial and academic hardware design projects can benefit from the use of the Custom Coprocessors Compilation (CCC) HLS behavioral synthesise, via the massive reduction in design and verification time. The CCC tool is built with formal compiler-compiler, Logic Programming and XML validation techniques, thus the generated RTL VHDL or Verilog models are provably-correct. In this work, we rapidly modeled CNNs in the ADA programming language, compiled and verified along with all the necessary testbenches in GNU ADA. Edge-detection, halftoning and morphological processing applications were prototyped, so as to evaluate the CCC HLS method, which was the main contribution of this work. The combination of Logic Programming and RDF validation techniques, as well as prototyping of CNN applications made this work unique.
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Papers by Dimitrios Amanatidis