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MDA 2023 International Conference on Mass Data Analysis of Images and Signals with Applications in Medicine, r/g/b Biotechnology, Food Industries and Dietetics, Biometry and Securitry, and Agriculture
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vertical-align:top; color:#666666; width:18.2981em; height:8.2379em;"> <iframe src="http://www.facebook.com/plugins/likebox.php?href=http%3A%2F%2Fwww.facebook.com%2Ffind-friends%2Findex.php%23%21%2Fpages%2FQuantitative-Measurement-of-Cellular-Events%2F276452592377930+&width=230&colorscheme=light&connections=0&stream=false&header=false&height=150" scrolling="no" frameborder="0" style="border:none; overflow:hidden; width:230px; height:150px;" allowTransparency="true"></iframe> </div> <p> </p> </div> <div class="org"> <div style="text-indent: 20px; vertical-align:top; color:#666666;width:18.2981em; height:6.2379em;"> <iframe src="http://www.facebook.com/plugins/likebox.php?href=http%3A%2F%2Fwww.facebook.com%2Ffind-friends%2Findex.php%23%21%2Fpages%2FData-Mining-Machine-Learning-Community%2F144294218954736+&width=230&colorscheme=light&connections=0&stream=false&header=false&height=85" scrolling="no" frameborder="0" style="border:none; overflow:hidden; width:230px; height:85px;" allowTransparency="true"></iframe> </div> </div> </div> <div id="content"> <div class="block containingfloat"> <div class="left noborder"> <h1>Tutorial Intelligent Image Interpretation and Computer Vision in Medicine, Biotechnology, Chemistry & Food Industry</h1> <h2>July 11th, 2022, New York / USA </h2> <p><b>Prof. Dr. Petra Perner</b>, Institut of Computer Vision and applied Computer Sciences, IBaI </p> <p align="justify"> Image interpretation systems are becoming increasingly popular in medical and industrial applications. The existing techniques lack robustness, accuracy, and flexibility. New strategies are necessary that can adapt to changing environmental conditions, user needs and process requirements. Introducing intelligent strategies into image interpretation systems can satisfy these requirements. Intelligent strategies provide a flexible and powerful methods for controlling the image processing process in all phases of an image interpretation system to derive information of the highest possible quality. Beyond this they offers different learning capabilities, for all phases of an image interpretation system, that satisfy different needs during the development process of an image interpretation system.</p> <p> The tutorial will give an introduction to intelligent image interpreation and computer vision. Different methods for image segementation, feature extraction and image interpretation will be presented. Application in Medicine, Biotechnology, Chemistry & Food Industry will be demonstrated.</p> <p align="justify">Participants will receive a stampend and signed certificate by IBaI for their participation in the tutorial and the tutorial material.</p> <h2>Content</h2> <ul> <p>Tutorial starts at 9:00 am and ends at 4:00 pm.</p> <li>Conventional Image Processing versus Intelligent Image Processing</li> <li>Intelligent Image Segmentation, Rule-based Image Segmentation, CBR Image Segmentation, CBR Object Matching</li> <li>Feature Extraction Learning based on Intelligent Strategies, Evolutional Strategies</li> <li>Case-based Reasoning for Image Interpretation</li> <li> Meta Learning of Image Processing Algorithm</li> <li>Applications in Medicine, Biotechnology, Chemistry & Food Industry</li> </ul> <h2>Lecturer</h2> <p align="justify">Petra Perner is the director of the Institute of Computer Vision and Applied Computer Sciences IBaI. Her research interest is image analysis and interpretation, machine learning, data mining, machine learning, image mining and case-based reasoning. Recently, she is working on various medical, chemical and biomedical applications, information management applications, technical diagnosis and e-commerce applications. She has published numerous scientific publications and patents and is often requested as a plenary speaker in distinct research fields as well as across disciplines. Her vision is to build intelligent flexible and robust data-interpreting systems that are inspired by the human case-based reasoning process.</p> </div> <div class="right"> <img class="pic" src="img/156_conference.jpg" alt="conference © Petra Perner" title="conference"/> <img class="pic" src="img/156_conference2.jpg" alt="conference © Fotolia" title="conference"/> <img class="pic" src="img/156_conference3.jpg" alt="conference © Petra Perner" title="conference"/> </div> </div> </div> </body> </html>