[B13] G.A. Papakostas, D.A. Karras, B.G. Mertzios, D. van Ormondt, and D. Graveron-Demilly, “Two-stage Evolutionary Quantification of in vivo MRS Metabolites”, in Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology, Q.N. Tran and H. R. Arabnia (Eds.), Elsevier/MK, vol. A, pp. 537-560, 2015.(DOI)

[B12] G.A. Papakostas, “Improving the Recognition Performance of Moment Features by Selection”, in Feature Selection for Data and Pattern Recognition, U. Stanczyk and L.C. Jain (Eds.), Studies in Computational Intelligence, vol. 584, pp. 305-327, Springer, 2015.(DOI)

[B11] E.D. Tsougenis, G.A. Papakostas and D.E. Koulouriotis, “Moment-based Image Watermarking: Principles, Perspectives and Challenges”, Encyclopedia of Information Science and Technology, (3rd Ed) Edited by Mehdi Khosrow-Pour, pp. 7202-7211, IGI Global, 2015.(DOI)

[B10] E.D. Tsougenis, G.A. Papakostas, “Should We Consider Adaptivity in Moment-based Image Wateramarking ?”, in Moments and Moment Invariants – Theory and Applications, G.A. Papakostas (Ed.), GCSR vol. 1, pp. 253-274, Science Gate Publishing, 2014.(DOI)

[B9] G.A. Papakostas, “Over 50 Years of Moments and Moment Invariants”, in Moments and Moment Invariants – Theory and Applications, G.A. Papakostas (Ed.), GCSR vol. 1, pp. 3-32, Science Gate Publishing, 2014.(DOI)

[B8] E.G. Karakasis, G.A. Papakostas and D.E. Koulouriotis, “Pattern Recognition Using Quaternion Color Moments”, in Pattern Recognition: Practices, Perspectives and Challenges, D.B. Vincent (Ed.), pp. 153-176, ISBN 978-1-62618-198-4, Nova Publishers, 2013.

[B7] G.A. Papakostas, D.E. Koulouriotis and V.D. Tourassis, “Feature Extraction Based on Wavelet Moments and Moment Invariants in Machine Vision Systems”,  in Machine Vision, F. Solari (Ed.), ISBN 978-953-51-0563-3, InTech, 2012.(DOI)

[B6] G.A. Papakostas, E.G. Karakasis and D.E. Koulouriotis, “Orthogonal Image Moment Invariants: Highly Discriminative Features for Pattern Recognition Applications”, in Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies, Vijay Kumar Mago and Nitin Bhatia (Eds.), pp. 34-52, ISBN 978-1613504291, IGI Global, 2012.(DOI)

[B5] G.A. Papakostas, D.E. Koulouriotis, A.S. Polydoros and V.D. Tourassis, “Evolutionary Feature Subset Selection for Pattern Recognition Applications”, in Evolutionary Algorithms, Eisuke Kita (Ed.), pp. 443-458, ISBN 978-953-307-171-8, InTech, 2011.(DOI)

[B4] G.A. Papakostas, D.E. Koulouriotis, E.G. Karakasis and V.D. Tourassis, “A General Framework for Computation of Biomedical Image Moments”, in Biomedical Engineering, Trends in Electronics, Communications and Software, Anthony N. Laskovski (Ed.), pp. 449-460, ISBN 978-953-307-475-7, InTech, 2011.(DOI)

[B3] G.A. Papakostas and D.E. Koulouriotis, “Classifying Patterns Using Fuzzy Cognitive Maps” in Fuzzy Cognitive Maps: Advances in Theory, Methodologies, Tools and Applications, M. Glykas (Ed.), pp. 291-306, ISBN: 978-3-642-03219-6, Springer, 2010.(DOI)

[B2] G.A. Papakostas, D.E. Koulouriotis and E.G. Karakasis, “Efficient 2-D DCT Computation from an Image Representation Point of View”, in Image Processing, Yung-Sheng Chen (Ed.), pp. 21-34, ISBN 978-3-902613-44-8, InTech, 2009.(DOI)

[B1] G. Papakostas, D.A. Karras, Y. Boutalis, B.G. Mertzios, “Efficient Computation of Moment Descriptors”, in Recent Advances in Applied Signals, Systems and Image Processing, D.A. Karras (Εd.), ISBN: 978-1-4020-8169-9, Springer, 2009.



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