BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Asia/Calcutta BEGIN:STANDARD DTSTART:19451014T230000 TZOFFSETFROM:+0630 TZOFFSETTO:+0530 TZNAME:IST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20220108T071832Z UID:95D6C791-7F6F-4B35-8EF2-2ABE2E98506A DTSTART;TZID=Asia/Calcutta:20211228T090000 DTEND;TZID=Asia/Calcutta:20211231T200000 DESCRIPTION:Artificial Intelligence(AI) makes computers automatically learn and respond without being explicitly programmed. Speech processing\, imag e processing\, weather predictions and other major signal processing appli cations are currently using machine learning techniques to automate the me chanism of processing of signals. Machine learning techniques share major part in the implementation of AI systems in signal processing especially f or healthcare. These technologies are showing their potential in getting s olutions to many bio medical applications like predicting cancer\, epilept ic seizure\, etc. Machine Learning techniques are more suitable because of the underlying mathematics is fairly straightforward regardless of the al gorithm used. The complexity and the mystery of algorithms lie in the amou nt of data process to get the interesting results. Hence\, there is a grea t need of knowing how AI is used for these purposes accompanied with signa l processing. The term "deep learning" refers to new methods and strategie s for generating the deep hierarchies of non-linear features by overcoming the problems with vanishing gradients\, allowing us to train architecture s with dozens of layers of non-linear hierarchical features. Deep learning is associated with learning not only deep non-linear hierarchical feature s\, but also learning to detect very long non-linear time dependencies in sequential data. This event presents the advance signal processing concept s and tools needed to apply Artificial intelligence in distributed areas. Acquire the knowledge and hands on experience of latest enhancements in de ep learning techniques. Latest techniques for capturing\, processing\, man ipulating\, learning and classifying signals will be discussed. Participan ts will have the familiarity of system design and development\, procedures \, architectures\, and applications for signal processing and Artificial i ntelligence. 18 sessions\, 2 Panel discussions and One poster presentation \n\nTopics\n\n- Artificial intelligence – Search Strategies\n- Machine L earning and its Applications\n- Artificial Intelligence Trends and Its Imp act\n- Recent advancements of AI in the field of Computer Vision\n- Artifi cial Intelligence in Speech Processing Applications\n- Optimization of Mac hine Learning techniques for signal processing applications.\n- Principles of Navigation Systems: Toy Car assembly\, Control and Communication\n- De ep Learning Concepts and Applications\n- Machine Learning for Wireless Sen or Networks\n- Medical Informatics and Biometrics with Machine Learning an d Deep Learning\n- Signal Processing and Artificial Intelligence for dysar thric speech\n- Artificial intelligence and Neuroscience: Past\, Present a nd Future\n- Bayesian Techniques for Local post-hoc XAI\n- Python for Mach ine Learning Algorithms\n- A panel discussion on Developments and challeng es in AI for signal processing during last decade\n- A panel discussion on Roles and Opportunities for Women in Signal Processing\n- Poster Presenta tion\n- Please visit the following link for more details\n- https://sps202 1.ieee-icmacc.org/\n\nBldg: Bachupally\, VNR Vignana Jyothi Institute of E ngineering and Technology\, Kukatpally\, Hyderabad\, Andhra Pradesh\, Indi a\, 500090\, Virtual: https://events.vtools.ieee.org/m/288904 LOCATION:Bldg: Bachupally\, VNR Vignana Jyothi Institute of Engineering and Technology\, Kukatpally\, Hyderabad\, Andhra Pradesh\, India\, 500090\, V irtual: https://events.vtools.ieee.org/m/288904 ORGANIZER:Priyanka.veeramosu@ieee.org SEQUENCE:1 SUMMARY:IEEE VNRVJIET SPS SBC / 4-Day Hybrid/SPS Seasonal School/ Recent Ad vances in Artificial Intelligence for Signal Processing in association wit h SPS and WIE AG IEEE Hyderabad Section URL;VALUE=URI:https://events.vtools.ieee.org/m/288904 X-ALT-DESC:Description: <br /><p>Artificial Intelligence(AI) makes computer s automatically learn and respond without being explicitly programmed. Spe ech processing\, image processing\, weather predictions and other major si gnal processing applications are currently using machine learning techniqu es to automate the mechanism of processing of signals. Machine learning te chniques share major part in the implementation of AI systems in signal pr ocessing especially for healthcare. These technologies are showing their p otential in getting solutions to many bio medical applications like predic ting cancer\, epileptic seizure\, etc. Machine Learning techniques are mor e suitable because of the underlying mathematics is fairly straightforward regardless of the algorithm used. The complexity and the mystery of algor ithms lie in the amount of data process to get the interesting results. He nce\, there is a great need of knowing how AI is used for these purposes a ccompanied with signal processing. The term "deep learning" refers to new methods and strategies for generating the deep hierarchies of non-linear f eatures by overcoming the problems with vanishing gradients\, allowing us to train architectures with dozens of layers of non-linear hierarchical fe atures. Deep learning is associated with learning not only deep non-linear hierarchical features\, but also learning to detect very long non-linear time dependencies in sequential data. This event presents the advance sign al processing concepts and tools needed to apply Artificial intelligence i n distributed areas. Acquire the knowledge and hands on experience of late st enhancements in deep learning techniques. Latest techniques for capturi ng\, processing\, manipulating\, learning and classifying signals will be discussed. Participants will have the familiarity of system design and dev elopment\, procedures\, architectures\, and applications for signal proces sing and Artificial intelligence. 18 sessions\, 2 Panel discussions and On e poster presentation&nbsp\;</p>\n<p><strong>Topics&nbsp\;</strong></p>\n< ul>\n<li>Artificial intelligence &ndash\; Search Strategies</li>\n<li>Mach ine Learning and its Applications</li>\n<li>Artificial Intelligence Trends and Its Impact</li>\n<li>Recent advancements of AI in the field of Comput er Vision</li>\n<li>Artificial Intelligence in Speech Processing Applicati ons</li>\n<li>Optimization of Machine Learning techniques for signal proce ssing applications.</li>\n<li>Principles of Navigation Systems: Toy Car as sembly\, Control and Communication</li>\n<li>Deep Learning Concepts and Ap plications</li>\n<li>Machine Learning for Wireless Senor Networks</li>\n<l i>Medical Informatics and Biometrics with Machine Learning and Deep Learni ng</li>\n<li>Signal Processing and Artificial Intelligence for dysarthric speech</li>\n<li>Artificial intelligence and Neuroscience: Past\, Present and Future</li>\n<li>Bayesian Techniques for Local post-hoc XAI</li>\n<li> Python for Machine Learning Algorithms</li>\n<li>A panel discussion on Dev elopments and challenges in AI for signal processing during last decade</l i>\n<li>A panel discussion on Roles and Opportunities for Women in Signal Processing&nbsp\;</li>\n<li>Poster Presentation&nbsp\;</li>\n<li><strong>P lease visit the following link for more details</strong></li>\n<li>https:/ /sps2021.ieee-icmacc.org/</li>\n</ul>\n<p><strong>&nbsp\;</strong></p> END:VEVENT END:VCALENDAR