[AUDITORY] [Call for paper] Special Session on Multimodal Signal Processing, IEEE ISCAS 2021 (Lin Wang )

Subject: [AUDITORY] [Call for paper] Special Session on Multimodal Signal Processing, IEEE ISCAS 2021 From: Lin Wang <lin.wang@xxxxxxxx> Date: Wed, 11 Nov 2020 23:51:22 +0000 --_000_VI1PR07MB3470395B9BE4E5E16F591897B9E80VI1PR07MB3470eurp_ Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable IEEE International Symposium on Circuits and Systems (ISCAS) 2021, Daegu, K= orea May 23-26, 2021 (1) Special Session: # 14.16 Multimodal Signal Processing Goal and Scope: With recent advance of sensing, computing, and communicatio= n capabilities, vast amount of multimodal data can be readily accessed. Thi= s fulfills the large training data demands of deep learning algorithms, and= accordingly various multimodal systems have been developed. As many previo= us works have reported, integrating data from multimodalities can yield imp= roved performance for target tasks. It is also confirmed that combining mul= timodal signals, including audio, visual, written documents, and vibrations= have been proven to yield higher accuracies on classification tasks and be= tter quality on generation tasks. Although the effectiveness of multimodal = signal processing has been confirmed, there remain several challenges to ta= ckle, including sensing device designs and hard-ware implementation methods= , as well as advanced signal processing and machine learning algorithms. Th= ese challenges should be jointly considered when searching optimal solution= s for multimodal signal processing. The goal of this special session is to = invite researchers from different fields to share their hardware/software d= esign experience on multimodal signal processing frameworks. We also look f= orward new modalities that can be potentially integrated. We hope to promot= e and explore some practical solutions and novel ideas for this research di= rection through this special session. (2) Schedule Submission Deadline: 16 November 2020 (https://iscas2021.org/) Notification of decision: 15 January 2021 (3) Organization Committee Yu Tsao, Academia Sinica, Taiwan Sabato Marco SiniscalchI, University of Enna, Italy Lin Wang, Queen Mary University of London, UK Xavier Alameda-Pineda, INRIA, France --_000_VI1PR07MB3470395B9BE4E5E16F591897B9E80VI1PR07MB3470eurp_ Content-Type: text/html; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable <html> <head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Diso-8859-= 1"> <style type=3D"text/css" style=3D"display:none;"> P {margin-top:0;margin-bo= ttom:0;} </style> </head> <body dir=3D"ltr"> <div style=3D"font-family: Calibri, Arial, Helvetica, sans-serif; font-size= : 12pt; color: rgb(0, 0, 0);"> IEEE International Symposium on Circuits and System= s (ISCAS) 2021<o:p>, Daegu, Korea</o:p> <o:p>May 23-26, 2021 </o:p> <o:p> </o:p> (1)       Special Session: # 14.16 Multimodal Signal Processing <o:p> </o= :p> Goal and Scope: With recent advance of sensing, computing, and communicat= ion capabilities, vast amount of multimodal data can be readily accessed. This fulfills the large training data demand= s of deep learning algorithms, and accordingly various multimodal systems h= ave been developed. As many previous works have reported, integrating data = from multimodalities can yield improved performance for target tasks. It is also confirmed that combining multimod= al signals, including audio, visual, written documents, and vibrations have= been proven to yield higher accuracies on classification tasks and better = quality on generation tasks. Although the effectiveness of multimodal signal processing has been confirmed, ther= e remain several challenges to tackle, including sensing device designs and= hard-ware implementation methods, as well as advanced signal processing an= d machine learning algorithms. These challenges should be jointly considered when searching optimal solutions f= or multimodal signal processing. The goal of this special session is to inv= ite researchers from different fields to share their hardware/software desi= gn experience on multimodal signal processing frameworks. We also look forward new modalities that can be pot= entially integrated. We hope to promote and explore some practical solution= s and novel ideas for this research direction through this special session.=      <o:p> </o:p> <o:p> </o:p> (2)       Schedule<o:p></o:p> Submission Deadline: 16 November 2020 (https://iscas2021.org/)<o:p> </o:p> <o:p>Notification of decision: 15 January 2021 </o:p> <o:p> </o:p> (3)       Organization Committee<o:p></o:p> Yu Tsao, Academia Sinica, Taiwan <o:p> </o:p> Sabato Marco SiniscalchI, University of Enna, Italy <o:p> </o:p> Lin Wang, Queen Mary University of London, UK <o:p> </o:p> Xavier Alameda-Pineda, INRIA, France<o:p> </o:p> </div> </body> </html> --_000_VI1PR07MB3470395B9BE4E5E16F591897B9E80VI1PR07MB3470eurp_--

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