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</o:shapelayout></xml><![endif]--></head><body lang=EL link="#0563C1" vlink="#954F72" style='word-wrap:break-word'><div class=WordSection1><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Dear Machine Learning, Computer Vision and Autonomous Systems Engineers, Scientists and Enthusiasts,<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>you are welcomed to register and attend the Web e-Course  on Computer Vision consisting of the following two CVML Web e-Course Modules on offer (total 22 lectures):<o:p></o:p></span></p><p class=MsoNoSpacing><span class=tadv-format-panel><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Neural Networks/Deep Learning</span></b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'> (14 Lectures), <a href="http://icarus.csd.auth.gr/neural-networks-and-deep-learning-web-module/">http://icarus.csd.auth.gr/neural-networks-and-deep-learning-web-module/</a><b><o:p></o:p></b></span></p><ol style='margin-top:0in' start=1 type=1><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Artificial Neural Networks. Perceptron<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Multilayer Perceptron. Backpropagation.<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Convolutional Neural Networks<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>1D Convolutional Neural Networks<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Deep Autoencoders<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Attention and Transformer Networks<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Recurrent Neural Networks. LSTMs<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Deep Object Detection<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Special topics in Object Detection<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Few-Shot Object Recognition<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Deep Semantic Image Segmentation<o:p></o:p></span></li><li class=MsoNoSpacing style='color:black;margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Adversarial Machine Learning<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Generative Adversarial Networks in Multimedia Creation<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l0 level1 lfo1'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Mathematical Brain Modeling<o:p></o:p></span></li></ol><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Machine Learning</span></b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>  (12 Lectures), <a href="http://icarus.csd.auth.gr/machine-learning-web-module/">http://icarus.csd.auth.gr/machine-learning-web-module/</a></span><span lang=EN-US><o:p></o:p></span></p><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>1)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Introduction to Machine Learning<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>2)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Data Clustering<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>3)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Distance-based Classification<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>4)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Decision Surfaces. Support Vector Machines<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>5)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Label Propagation <o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>6)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Dimensionality Reduction<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>7)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Graph-based Dimensionality Reduction<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>8)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Kernel Methods<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>9)<span style='font:7.0pt "Times New Roman"'>      </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Bayesian Learning<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>10)<span style='font:7.0pt "Times New Roman"'>   </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Parameter Estimation<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>11)<span style='font:7.0pt "Times New Roman"'>   </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Hypothesis Testing<o:p></o:p></span></h4><h4 style='margin-left:.25in;text-indent:-.25in;mso-list:l2 level1 lfo2'><![if !supportLists]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'><span style='mso-list:Ignore'>12)<span style='font:7.0pt "Times New Roman"'>   </span></span></span><![endif]><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:windowtext;font-style:normal'>Syntactic Pattern Recognition<o:p></o:p></span></h4><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Around 50% of the lectures provide free access to the full lecture pdf!<o:p></o:p></span></b></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>You can find sample Web e-Course Module material to make up your mind and/or can perform CVML Web e-Course registration in:<o:p></o:p></span></b></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><a href="http://icarus.csd.auth.gr/cvml-web-lecture-series/">http://icarus.csd.auth.gr/cvml-web-lecture-series/</a><o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>For questions, please contact: Ioanna Koroni <<a href="mailto:koroniioanna@csd.auth.gr">koroniioanna@csd.auth.gr</a>><o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>More information on this Web e-course</span></b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>: This Web e-Course Computer Vision material that can cover a semester course, but you can master it in approximately 1 month. <b><o:p></o:p></b></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:black'>Course materials are at senior undergraduate/MSc level in a CS, CSE, EE or ECE or related Engineering or Science Department. Their structure, level and offer are completely different from what you can find in either Coursera or Udemy. </span><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>CVML Web e-Course Module materials<span style='color:black'> typically consist of: a) a lecture pdf/ppt, b) lecture </span>self-assessment <span style='color:black'>understanding questionnaire and lecture video, programming exercises, tutorial exercises (for several modules/lectures)  and overall course module satisfaction questionnaire.<o:p></o:p></span></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Asynchronous tutor support will be provided in case of questions.<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Course materials have been very successfully used in many top conference keynote speeches/tutorials worldwide and in short courses, summer schools, semester courses delivered by AIIA Lab physically or on-line from 2018 onwards, attracting many hundreds of registrants. <o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>More information on other CVML Web e-course</span></b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>: Several other Web e-Course Modules are  offered on Deep Learning, Computer Vision, Autonomous Systems, Signal/Image/Video Processing, Human-centered Computing, Social Media, Mathematical Foundations, CVML SW tools.<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>See: <a href="http://icarus.csd.auth.gr/cvml-web-lecture-series/">http://icarus.csd.auth.gr/cvml-web-lecture-series/</a><o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>You can combine CVML Web e-Course Modules to create CVML Web e-Courses (typically consisting of 16 lectures) of your own choice that cater your personal education needs.<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif;color:black'>Each </span><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>CVML Web e-Course you will create (typically 16 lectures) provides you material that can cover a semester course, but you can master it in approximately 1 month.<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Academic/Research/Industry offer and arrangements<o:p></o:p></span></b></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Special arrangements can be made to offer the material of these CVML Web e-Course Modules at University/Department/Company level: <o:p></o:p></span></p><ul style='margin-top:0in' type=disc><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l3 level1 lfo3'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>by granting access to the material to University/research/industry lecturers to be used as an aid in their teaching, <o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l3 level1 lfo3'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>by enabling class registration in CVML Web e-Courses<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l3 level1 lfo3'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>by delivering such live short courses physically or on-line by Prof. Ioannis Pitas<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l3 level1 lfo3'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>by combinations of the above.<o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l3 level1 lfo3'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>The <a href="https://www.i-aida.org/">AIDA</a> students are entitled 50% discount for CVML Web e-Course registration.<o:p></o:p></span></li></ul><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>The CVML Web e-Course is organized by Prof. I. Pitas, IEEE and EURASIP fellow, Coordinator of International AI Doctoral Academy (AIDA), past Chair of the IEEE SPS Autonomous Systems Initiative, <o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece, Coordinator of the European Horizon2020<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He has 34100+ citations to his work  and h-index 87+.<o:p></o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>The informatics Department at AUTH ranked 106th internationally in the field of Computer Science for 2019 in the Leiden Ranking list<span style='color:black'><o:p></o:p></span></span></p><p class=MsoNoSpacing><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'><o:p> </o:p></span></p><p class=MsoNoSpacing><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Relevant links:<o:p></o:p></span></b></p><ol style='margin-top:0in' start=1 type=1><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Prof. I. Pitas: <a href="https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el">https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el</a><o:p></o:p></span></b></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><b><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>International AI Doctoral Academy (AIDA): <a href="https://www.i-aida.org/">https://www.i-aida.org/</a><o:p></o:p></span></b></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Horizon2020 EU funded R&D project Aerial-Core: <a href="https://aerial-core.eu/">https://aerial-core.eu/</a><o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Horizon2020 EU funded R&D project Multidrone: <a href="https://multidrone.eu/">https://multidrone.eu/</a><o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>Horizon2020 EU funded R&D project AI4Media: <a href="https://ai4media.eu/">https://ai4media.eu/</a><o:p></o:p></span></li><li class=MsoNoSpacing style='margin-left:-.25in;mso-list:l1 level1 lfo4'><span lang=EN-US style='font-size:11.0pt;font-family:"Calibri",sans-serif'>AIIA Lab: <a href="https://aiia.csd.auth.gr/">https://aiia.csd.auth.gr/</a><o:p></o:p></span></li></ol><p class=MsoPlainText><span lang=EN-US style='color:windowtext'><o:p> </o:p></span></p><p class=MsoPlainText><span lang=EN-US>Sincerely yours</span><span lang=EN-US style='color:windowtext'><o:p></o:p></span></p><p class=MsoPlainText><span lang=EN-US>Prof. I. Pitas<o:p></o:p></span></p><p class=MsoPlainText><span lang=EN-US>Director of the Artificial Intelligence and Information analysis Lab (AIIA</span><span lang=EN-US style='color:windowtext'> </span><span lang=EN-US>Lab)</span><span lang=EN-US style='color:windowtext'><o:p></o:p></span></p><p class=MsoPlainText><span lang=EN-US>Aristotle University of Thessaloniki, Greece<o:p></o:p></span></p><p class=MsoPlainText><span lang=EN-US><o:p> </o:p></span></p><p class=MsoPlainText><span lang=EN-US>Post scriptum: To stay current on CVML matters, you may want to register to</span><span lang=EN-US style='color:windowtext'> </span><span lang=EN-US>the CVML email list, following instructions in</span><span lang=EN-US style='color:windowtext'> </span><span lang=EN-US><a href="https://lists.auth.gr/sympa/info/cvml">https://lists.auth.gr/sympa/info/cvml</a></span><o:p></o:p></p></div></body></html>