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Publications

AR Team > Publications
2017

Parallel Pattern Classification Utilizing CPU Based Kernelized Slackmin Algorithm

Papakostas, G. A., Diamantaras, K. I., & Papadimitriou, T. (2017). Parallel pattern classification utilizing GPU-based kernelized Slackmin algorithm. Journal of Parallel and Distributed Computing, 99, 90-99.

FarmAR, a farmer’s augmented reality application based on semantic web

Katsaros, A., & Keramopoulos, E. (2017, September). FarmAR, a farmer's augmented reality application based on semantic web. In Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), 2017 South Eastern European (pp. 1-6). IEEE.

Sentiment Analysis Leveraging Emotions and Word Embeddings

Giatsoglou, M., Vozalis, M. G., Diamantaras, K., Vakali, A., Sarigiannidis, G., & Chatzisavvas, K. C. (2017). Sentiment analysis leveraging emotions and word embeddings. Expert Systems with Applications, 69, 214-224.

Airfare Prices Prediction Using Machine Learning Techniques

Tziridis, K., Kalampokas, T., Papakostas, G. A., & Diamantaras, K. I. (2017, August). Airfare prices prediction using machine learning techniques. In Signal Processing Conference (EUSIPCO), 2017 25th European (pp. 1036-1039). IEEE.

Kernel subspace methods for pattern classification

Exploring the effect of Data Reduction on Neural Network and Support Vector Machine Classification

Adaptive Margin Slack Minimization in RKHS for Classification

Yu, Y., Diamantaras, K. I., McKelvey, T., & Kung, S. Y. (2016, March). Adaptive margin slack minimization in RKHS for classification. In Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on (pp. 2319-2323). IEEE.

Efficient Support Vector Machine Classification using Prototype Selection and Generation

Ougiaroglou, S., Diamantaras, K. I., & Evangelidis, G. (2016, September). Efficient Support Vector Machine Classification Using Prototype Selection and Generation. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 328-340). Springer International Publishing.

Mobile Augmented Reality Innovative Learning (mARIL) Model: Extending the SCORM e-Learning Model with Augmented Reality Features

M. Delianidi, C. Ilioudis, K. Theodorou, “Mobile Augmented Reality Innovative Learning (mARIL) Model: Extending the SCORM e-Learning Model with Augmented Reality Features”, 9th Conference on Informatics in Education 2017, pp. 467-478, Athens 2017

Cultivation Optimization Using Augmented Reality

Katsaros, A., Keramopoulos, E. (2017), & Salampasis, M. Cultivation Optimization Using Augmented Reality. In HAICTA (pp. 805-811).