BEGIN:VCALENDAR VERSION:2.0 PRODID:Linklings LLC BEGIN:VTIMEZONE TZID:Australia/Melbourne X-LIC-LOCATION:Australia/Melbourne BEGIN:DAYLIGHT TZOFFSETFROM:+1000 TZOFFSETTO:+1100 TZNAME:AEDT DTSTART:19721003T020000 RRULE:FREQ=YEARLY;BYMONTH=4;BYDAY=1SU END:DAYLIGHT BEGIN:STANDARD DTSTART:19721003T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 TZNAME:AEST RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20240214T070244Z LOCATION:Exhibition Hall 1\, Level 2 (Exhibition Centre) DTSTART;TZID=Australia/Melbourne:20231213T110000 DTEND;TZID=Australia/Melbourne:20231213T173000 UID:siggraphasia_SIGGRAPH Asia 2023_sess202_pos_197@linklings.com SUMMARY:Recognition-Independent Handwritten Text Alignment Using Lightweig ht Recurrent Neural Network DESCRIPTION:Poster\n\nKarina Korovai, Dmytro Zhelezniakov, and Olga Radyvo nenko (Samsung R&D Institute Ukraine); Oleg Yakovchuk (Samsung R&D Institu te Ukraine, National Technical University of Ukraine "Igor Sikorsky Kyiv P olytechnic Institute"); and Ivan Deriuga and Nataliya Sakhnenko (Samsung R &D Institute Ukraine)\n\nA novel approach to improve handwriting legibilit y by straightening the written content. It may be used for aligning text a cross different languages and doesn't need prior handwriting recognition.\ n\nRegistration Category: Full Access, Business & Innovation Symposium Acc ess, Exhibit & Experience Access, Enhanced Access, Trade Exhibitor, Experi ence Hall Exhibitor URL:https://asia.siggraph.org/2023/full-program?id=pos_197&sess=sess202 END:VEVENT END:VCALENDAR