Software
Downloads - Software in Matlab
- Matlab Central
- A speech/music discriminator based on RMS and zero-crossings
- This code implements a method for a speech/music discriminator based on RMS and zero-crossings [1].
- [1]. C. Panagiotakis and G. Tziritas, A speech/music discriminator based on RMS and zero-crossings, IEEE Transactions on Multimedia, Vol. 7, No. 1, Feb. 2005.
- This code implements a method for a speech/music discriminator based on RMS and zero-crossings [1].
- Successive Group Selection for Microaggregation
- A method that solves the statistical disclosure control (Microaggregation) [2]
- You can download the 216 synthetic datasets that have been used in the article [2].
- [2] C. Panagiotakis and G. Tziritas, Successive Group Selection for Microaggregation, IEEE Trans. on Knowledge and Data Engineering, vol.25, no.5, pp.1191-1195, May 2013.
- Local Community Detection via a Flow Propagation (FlowPro) method
- FlowPro finds the community of a node in a complex network without the knowledge of the entire graph [3], [4]
- [3] C. Panagiotakis, H. Papadakis and P. Fragopoulou, FlowPro: A Flow Propagation Method for Single Community Detection, IEEE Consumer Communications and Networking Conference, 2014.
- [4] C. Panagiotakis, H. Papadakis and P. Fragopoulou, Local Community Detection without the Knowledge of the Entire Graph via a Flow Propagation method , Social Networks, 2014.
- Signal Segmentation and Modelling
- Simultaneous Signal Segmentation and Modelling based on Equipartition Principle [5]
- [5] C. Panagiotakis and G. Tziritas, Simultaneous Segmentation and Modelling of Signals based on an Equipartition Principle, 20th International Conference for Pattern Recognition (ICPR), 2010.
- Community Detection in Graph
- Community Detection in Graphs Using Synthetic Coordinates [6]
- [6]. H. Papadakis, C. Panagiotakis and P. Fragopoulou, Distributed detection of communities in complex networks using synthetic coordinates, Journal of Statistical Mechanics, 2014
- Simultaneous Signal Segmentation and Modelling based on Equipartition Principle [5]
- Video Synophis
- Video Synopsis - Key frames Selection based on a Distortion Minimization method [7]
- [7]. C. Panagiotakis, N. Ovsepian and E. Michael, Video Synopsis based on a Sequential Distortion Minimization Method, International Conference on Computer Analysis of Images and Patterns, 2013.
- Video Synopsis - Key frames Selection based on a Distortion Minimization method [7]
- Filters for Curvilinear Enhancement
- Step filtering and Polynomial filtering for enhancement of partial curvilinear structures [8]
- [8]. C. Panagiotakis, E. Kokinou and A. Sarris, Curvilinear Structure Enhancement and Detection in Geophysical Images, IEEE Trans. on Geoscience and Remote Sensing, vol. 49, no. 6, pp. 2040-2048, 2011.
- Step filtering and Polynomial filtering for enhancement of partial curvilinear structures [8]
- Point Clustering via Voting Maximization
- Implementation of CVR and CVR-LMV [9] methods for clustering
- [9]. C. Panagiotakis, Point Clustering via Voting Maximization, Journal of Classification, vol. 32, no. 2, pp. 212-240, 2015.
- Implementation of CVR and CVR-LMV [9] methods for clustering
- Beat Synchronous Dance Animation
- Implementation of Beat Synchronous Dance Animation method [10]
- [10]. C. Panagiotakis, Andre Holzapfel, Damien Michel, and Antonis Argyros, Beat Synchronous Dance Animation based on Periodic Motion and Music Tempo Analysis, International Symposium on Visual Computing, 2013.
- Implementation of Beat Synchronous Dance Animation method [10]
- Modelling of 2D Shapes with Ellipses
- Implementation of AEFA,DEFA and EMAR [11] methods for Modelling of 2D Shapes with Ellipses
- [11]. C. Panagiotakis and A. Argyros, Parameter-free Modelling of 2D Shapes with Ellipses, Pattern Recognition, 2015.
- Implementation of AEFA,DEFA and EMAR [11] methods for Modelling of 2D Shapes with Ellipses
- VOLEI method
- Unsupervised Detection of Topographic Highs [12]
- [12]. C. Panagiotakis and E. Kokinou, Unsupervised Detection of Topographic Highs with Arbitrary Basal Shapes Based on Volume Evolution of Isocontours, Computers & Geosciences, vol. 102, pp. 22-33, 2017.
- You can download the 180 synthetic DEMs that have been used in the article [12].
- Unsupervised Detection of Topographic Highs [12]
- Detection of Geological Faults
- Automatic enhancement and identification of geological fault structures [13-14]
- [13] C. Panagiotakis and E. Kokinou, Automatic enhancement and detection of active sea faults from bathymetry,International Conference on Pattern Recognition, 2014.
- [14] C. Panagiotakis and E. Kokinou, Linear Pattern Detection of Geological Faults via a Topology and Shape Optimization Method, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 1, pp. 3-11, 2015.
- Automatic enhancement and identification of geological fault structures [13-14]
- MUCOS method
- Detecting Common Actions in Motion Capture Data and Videos
- [15] Panagiotakis, C., Papoutsakis, K., & Argyros, A. (2018). A graph-based approach for detecting common actions
- in motion capture data and videos. Pattern Recognition, 79, 1-11.
- Detecting Common Actions in Motion Capture Data and Videos
- PMUCOS method
- Periodicity Detection in Videos
- [16] C. Panagiotakis, G. Karvounas, and A. Argyros, Unsupervised Detection of Periodic Segments in Videos, IEEE International Conference on Image Processing, 2018..
- Periodicity Detection in Videos
- SEG-SELF method
- Cell Segmentation
- [17] C. Panagiotakis and A. Argyros, Cell Segmentation via Region-based Ellipse Fitting, IEEE International Conference on Image Processing, 2018.
- Cell Segmentation
- SCoR Recommender System
- A Synthetic Coordinate based Recommender System
- [18] H. Papadakis, C. Panagiotakis and P. Fragopoulou, SCoR: A Synthetic Coordinate based Recommender System, Expert Systems with Applications, vol. 79, pp.8-19, 2017.
- A speech/music discriminator based on RMS and zero-crossings
- JAVA
- You can download the executable for Community Detection Using Synthetic Coordinates and the synthetic datasets used in [6].
- USAGE:
- run: java -jar SCCD.jar graph-filename
- output: coms.txt: Each line holds the ids of all nodes of a community separated by space
- USAGE:
- You can download the executable for Community Detection Using Synthetic Coordinates and the synthetic datasets used in [6].