[AUDITORY] CFP -- Special Issue on Deep Learning for Acoustic Sensor Array Processing (DL-ASAP) (Carlo Drioli )


Subject: [AUDITORY] CFP -- Special Issue on Deep Learning for Acoustic Sensor Array Processing (DL-ASAP)
From:    Carlo Drioli  <carlo.drioli@xxxxxxxx>
Date:    Tue, 5 Oct 2021 14:11:21 +0200

--------------84067624DAA701F696A27B8C Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit Dear List, Submissions are now open for a special issue of Pattern Recognition Letters on Deep Learning for Acoustic Sensor Array Processing (DL-ASAP). Please find the CfP in Elsevier PRL web pages at: https://www.journals.elsevier.com/pattern-recognition-letters/call-for-papers/deep-learning-for-acoustic-sensor-array-processing-dl-asap *Submission deadline: March 20, 2022* You are welcome to distribute this call to your research team members. The proposed special issue aims to present recent advances in the development of artificial intelligence and deep learning methods for acoustic sensor array processing emphasizing the associated theory, models, and applications. Automatic computer audition and microphone arrays need novel methods that use modern deep learning array processing addressing the challenges raised by real-life applications. The Special Issue welcomes research papers covering innovative learning-based approaches, theoretical advances, technological improvements, and novel applications in the field. The particular topics of interest include, but are not limited to: - Machine learning models and algorithms for acoustic sensing - Detection and recognition of acoustic events - Deep learning for localization in noisy and reverberant environments - Data-driven tracking moving sources - Deep learning for acoustic scene analysis - Source separation and audio signal enhancement with expert systems - Voice recognition - Machine learning acoustic source identification - Binaural processing and artificial intelligence - Distributed acoustic sensor networks with expert systems - Deep learning for simultaneous localization and mapping (SLAM) - Source and scene classification Kind regards, The Guest Editors --------------84067624DAA701F696A27B8C Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: 7bit <html><head> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"> </head> <body> Dear List,<br> <br> Submissions are now open for a special issue of Pattern Recognition Letters on Deep Learning for Acoustic Sensor Array Processing (DL-ASAP). Please find the CfP in Elsevier PRL web pages at:<br> <br> <a class="moz-txt-link-freetext" href="https://www.journals.elsevier.com/pattern-recognition-letters/call-for-papers/deep-learning-for-acoustic-sensor-array-processing-dl-asap">https://www.journals.elsevier.com/pattern-recognition-letters/call-for-papers/deep-learning-for-acoustic-sensor-array-processing-dl-asap</a><br> <br> <b>Submission deadline: March 20, 2022</b><br> <br> You are welcome to distribute this call to your research team members.<br> <br> The proposed special issue aims to present recent advances in the development of artificial intelligence and deep learning methods for acoustic sensor array processing emphasizing the associated theory, models, and applications. Automatic computer audition and microphone arrays need novel methods that use modern deep learning array processing addressing the challenges raised by real-life applications. The Special Issue welcomes research papers covering innovative learning-based approaches, theoretical advances, technological improvements, and novel applications in the field.<br> <br> The particular topics of interest include, but are not limited to:<br> <br> - Machine learning models and algorithms for acoustic sensing<br> - Detection and recognition of acoustic events<br> - Deep learning for localization in noisy and reverberant environments<br> - Data-driven tracking moving sources<br> - Deep learning for acoustic scene analysis<br> - Source separation and audio signal enhancement with expert systems<br> - Voice recognition<br> - Machine learning acoustic source identification<br> - Binaural processing and artificial intelligence<br> - Distributed acoustic sensor networks with expert systems<br> - Deep learning for simultaneous localization and mapping (SLAM)<br> - Source and scene classification<br> <br> Kind regards,<br> The Guest Editors<br> <pre class="moz-signature" cols="72"> </pre> </body> </html> --------------84067624DAA701F696A27B8C--


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