{"id":783,"date":"2020-10-21T18:13:51","date_gmt":"2020-10-21T17:13:51","guid":{"rendered":"http:\/\/www.eledia.org\/e-air\/?p=783"},"modified":"2020-10-21T18:17:40","modified_gmt":"2020-10-21T17:17:40","slug":"ieeetap-si-2021","status":"publish","type":"post","link":"https:\/\/www.eledia.org\/e-air\/ieeetap-si-2021\/","title":{"rendered":"IEEE T-AP Special Issue on “Artificial Intelligence: New Frontiers in Real\u2010Time Inverse Scattering and Electromagnetic Imaging”"},"content":{"rendered":"\n
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The IEEE Transactions on Antennas and Propagation<\/a> has just announced an upcoming Special issue to appear in November 2021 on Artificial Intelligence: New Frontiers in Real\u2010Time Inverse Scattering and Electromagnetic Imaging<\/strong> which will be guest edited by Manuel ARREBOLA, Maokun LI, Marco SALUCCI. Please find below additional information and important dates and visit the dedicated web page<\/a> for submission procedures.<\/p>\n\n\n\n

Guest Editors<\/span><\/strong><\/h3>\n\n\n\n

Manuel ARREBOLA<\/strong>, Universidad de Oviedo, Spain (arrebola@uniovi.es<\/a>)
Maokun LI<\/strong>, Tsinghua University (maokunli@tsinghua.edu.cn<\/a>)
Marco SALUCCI<\/strong>, University of Trento (marco.salucci@unitn.it<\/a>)<\/p>\n\n\n\n

Outline<\/span><\/strong><\/h3>\n\n\n\n

Understanding and solving complex problems in the physical world has been an intelligent endeavor of humankind. Moreover, the study of artificial intelligence embodies the dream of designing machines like humans. Research in deep learning (DL) techniques has attracted much attention in many application areas. With the help of big data technology, massive parallel computing, and fast optimization algorithms, DL has greatly improved the performance of many problems in the speech and image research, power transportation networks or bio\u2010electromagnetics, among others. Nowadays, DL is rapidly emerging in the antennas and propagation community as an extremely powerful paradigm for solving high\u2010complexity electromagnetic inverse scattering (IS) and imaging problems with unprecedented computational efficiency without reducing the accuracy and therefore reliability. As a matter of fact, DL is a promising solution to achieve accurate pixel\u2010wise reconstructions with real\u2010time estimation performance, a desirable feature in many applications such as biomedical imaging, works of art and archaeological inspection, industrial non destructive testing and evaluation, trough\u2010the\u2010wall imaging, and subsurface imaging. With the spreading of DL techniques, improvement in learning capacity may allow machines to \u201clearn\u201d from a large amount of physical data and \u201cmaster\u201d the physical laws in certain controlled boundary conditions. In the long run, a hybridization of fundamental physical principles with \u201cknowledge\u201d from big data could unleash numerous engineering applications that used to be impossible due to the limit of data information and ability of computation. As a result, more advanced IS and electromagnetic imaging techniques can be developed with improved accuracy, robustness, and computational efficiency. The objective of this Special Issue is to report recent advancements in theory and applications of artificial intelligence and DL to solve electromagnetic IS and imaging problems within the research scope of Antennas and Propagation with extremely fast but reliable techniques. With this Special Issue, we hope to bring more attention and research efforts in our society to this emerging multi\u2010disciplinary field, resulting in an evolution of the state of the art. <\/p>\n\n\n\n

Important Dates<\/span><\/strong><\/h3>\n\n\n\n
  • Submission: March 31, 2021<\/span><\/strong><\/li>
  • Final decision: August 31, 2021<\/strong><\/li>
  • Publication: November 30, 2021<\/strong><\/li><\/ul>\n\n\n\n

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    The IEEE Transactions on Antennas and Propagation has just announced an upcoming Special issue to appear in November 2021 on Artificial Intelligence: New Frontiers in Real\u2010Time Inverse Scattering and Electromagnetic Imaging which will be guest edited by Manuel ARREBOLA, Maokun LI, Marco SALUCCI. Please find below additional information and important dates and visit the dedicated […]<\/p>\n","protected":false},"author":3,"featured_media":796,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[18],"tags":[22,23,21],"_links":{"self":[{"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/posts\/783"}],"collection":[{"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/comments?post=783"}],"version-history":[{"count":13,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/posts\/783\/revisions"}],"predecessor-version":[{"id":800,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/posts\/783\/revisions\/800"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/media\/796"}],"wp:attachment":[{"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/media?parent=783"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/categories?post=783"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.eledia.org\/e-air\/wp-json\/wp\/v2\/tags?post=783"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}