BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT DTSTART:20240310T030000 TZOFFSETFROM:-0800 TZOFFSETTO:-0700 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:PDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20241103T010000 TZOFFSETFROM:-0700 TZOFFSETTO:-0800 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:PST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240413T021622Z UID:D1EF42D0-A0A0-4EE0-96E1-B81613AAFCA9 DTSTART;TZID=America/Los_Angeles:20240410T113000 DTEND;TZID=America/Los_Angeles:20240410T140000 DESCRIPTION:Abstract: The performance of deep learning (DL) empowered wirel ess communications\, networking\, and sensing depends on the availability of sufficient high-quality radio frequency (RF) data\, which is more diffi cult and expensive to collect than other types. To overcome this obstacle\ , we propose several AIGC approaches to generate synthetic RF data labeled with specified human activities for multiple wireless sensing platforms\, such as WiFi\, RFID\, mmWave radar\, including a conditional Recurrent Ge nerative Adversarial Network (R-GAN) approach and diffusion model based ap proaches. The high quality of the generated RF data is validated by metric s of Structural Similarity Index (SSIM) and Frechet Inception Distance (FI D)\, as well as representative downstream tasks of human activity recognit ion (HAR)\, where the model trained with sufficient synthesized data outpe rforms the model trained by real data.\n\n[]\n\nBio: Shiwen Mao (S'99-M'04 -SM'09-F'19) is a Professor and Earle C. Williams Eminent Scholar\, and Di rector of the Wireless Engineering Research and Education Center at Auburn University. Dr. Mao's research interest includes wireless networks\, mult imedia communications\, and smart grid. He is the editor-in-chief of IEEE Transactions on Cognitive Communications and Networking. He received the I EEE ComSoc MMTC Outstanding Researcher Award in 2023\, the 2023 SEC Facult y Achievement Award for Auburn\, the IEEE ComSoc TC-CSR Distinguished Tech nical Achievement Award in 2019\, the Auburn University Creative Research & Scholarship Award in 2018\, the NSF CAREER Award in 2010\, and several s ervice awards from IEEE ComSoc. He is a co-recipient of several best journ al and conference paper awards from the IEEE.\n\nAgenda: \n11:30AM-12:00PM : Lunch & networking\n\n12:00PM-1:30PM: Talk and Q&A\n\nRoom: Auditorium\, Bldg: Building Q\, 6455 Lusk Blvd\, San Diego\, California\, United State s\, 92121 LOCATION:Room: Auditorium\, Bldg: Building Q\, 6455 Lusk Blvd\, San Diego\, California\, United States\, 92121 ORGANIZER:maliangp@yahoo.com SEQUENCE:71 SUMMARY:Artificial Intelligence Generated Content for RF Sensing URL;VALUE=URI:https://events.vtools.ieee.org/m/412663 X-ALT-DESC:Description: <br /><p><strong>Abstract:</strong>&nbsp\; The perf ormance of deep learning (DL) empowered wireless communications\, networki ng\, and sensing depends on the availability of sufficient high-quality ra dio frequency (RF) data\, which is more difficult and expensive to collect than other types. To overcome this obstacle\, we propose several AIGC app roaches to generate synthetic RF data labeled with specified human activit ies for multiple wireless sensing platforms\, such as WiFi\, RFID\, mmWave radar\, including a conditional Recurrent Generative Adversarial Network (R-GAN) approach and diffusion model based approaches. The high quality of the generated RF data is validated by metrics of Structural Similarity In dex (SSIM) and Frechet Inception Distance (FID)\, as well as representativ e downstream tasks of human activity recognition (HAR)\, where the model t rained with sufficient synthesized data outperforms the model trained by r eal data.</p>\n<p><strong><img src="https://events.vtools.ieee.org/vtools_ ui/media/display/9227c83d-fcb5-4e2a-83d0-b1ea7a15e080" alt="" width="200" height="300"></strong></p>\n<p><strong>Bio:&nbsp\;</strong>Shiwen Mao (S'9 9-M'04-SM'09-F'19) is a Professor and Earle C. Williams Eminent Scholar\, and Director of the Wireless Engineering Research and Education Center at Auburn University. Dr. Mao's research interest includes wireless networks\ , multimedia communications\, and smart grid. He is the editor-in-chief of IEEE Transactions on Cognitive Communications and Networking.&nbsp\; He r eceived the IEEE ComSoc MMTC Outstanding Researcher Award in 2023\, the 20 23 SEC Faculty Achievement Award for Auburn\, the IEEE ComSoc TC-CSR Disti nguished Technical Achievement Award in 2019\, the Auburn University Creat ive Research &amp\; Scholarship Award in 2018\, the NSF CAREER Award in 20 10\, and several service awards from IEEE ComSoc. He is a co-recipient of several best journal and conference paper awards from the IEEE.</p><br />< br />Agenda: <br /><p>11:30AM-12:00PM: Lunch &amp\; networking</p>\n<p>12: 00PM-1:30PM: Talk and Q&amp\;A</p>\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR