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PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:America/New_York
BEGIN:DAYLIGHT
DTSTART:20230312T030000
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TZOFFSETTO:-0400
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BEGIN:STANDARD
DTSTART:20221106T010000
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BEGIN:VEVENT
DTSTAMP:20221205T015608Z
UID:E0A09AA1-8474-491E-BF5C-06F2E995BECC
DTSTART;TZID=America/New_York:20221201T170000
DTEND;TZID=America/New_York:20221201T183000
DESCRIPTION:This seminar will cover topics including:\n\n- Devices for Blin
 d People\, Amputees\, People with Severe Disability\n- Control of Applianc
 es Through sEMG and EOG\, Rehabilitation Through Serious Games\n- Use of I
 nternet of Things (IoT) for Human Activity Recognition (HAR) Based on Conv
 olutional Neural Network (CNN)\n- Robots for Interaction with Children wit
 h ASD and Down Syndrome\n- Respiratory Rate Estimation Through Deep Learni
 ng Applied to Photoplethysmogram\n- COVID Detection Through Recurrent Neur
 al Networks (RNN) and Deep Learning (DL)\n- Several Applications with Brai
 n-Computer Interfaces (BCIs) Based on Electroencephalography (EEG)\n\nSpea
 ker(s): Dr. Teodiano Freire Bastos-Filho\, \n\nRoom: 105\, Bldg: Eric Pali
 n Hall (EPH)\, 87 Gerrard St E\, Toronto\, Ontario\, Canada\, M5B 2M2\, Vi
 rtual: https://events.vtools.ieee.org/m/334682
LOCATION:Room: 105\, Bldg: Eric Palin Hall (EPH)\, 87 Gerrard St E\, Toront
 o\, Ontario\, Canada\, M5B 2M2\, Virtual: https://events.vtools.ieee.org/m
 /334682
ORGANIZER:mehnaz.shokrollahi.m@ieee.org
SEQUENCE:6
SUMMARY:Advances in Neuroscience at UFES/Brazil
URL;VALUE=URI:https://events.vtools.ieee.org/m/334682
X-ALT-DESC:Description: <br /><p>This seminar will cover topics including:<
 /p>\n<ul>\n<li>Devices for Blind People\, Amputees\, People with Severe Di
 sability</li>\n<li>Control of Appliances Through sEMG and EOG\, Rehabilita
 tion Through Serious Games</li>\n<li>Use of Internet of Things (IoT) for H
 uman Activity Recognition (HAR) Based on Convolutional Neural Network (CNN
 )</li>\n<li>Robots for Interaction with Children with ASD and Down Syndrom
 e</li>\n<li>Respiratory Rate Estimation Through Deep Learning Applied to P
 hotoplethysmogram</li>\n<li>COVID Detection Through Recurrent Neural Netwo
 rks (RNN) and Deep Learning (DL)</li>\n<li>Several Applications with Brain
 -Computer Interfaces (BCIs) Based on Electroencephalography (EEG)</li>\n</
 ul>
END:VEVENT
END:VCALENDAR