Subject: [AUDITORY] Call for Special Issue "Pattern recognition in multimodal information analysis: observation, extraction, classification, and interpretation" [Pattern Recognition Letters] From: Daniele Salvati <daniele.salvati@xxxxxxxx> Date: Thu, 1 Feb 2024 10:26:14 +0100--------------dZl3lXV6so0lMYLNwG2tNqB4 Content-Type: text/plain; charset=UTF-8; format=flowed Content-Transfer-Encoding: quoted-printable X-MIME-Autoconverted: from 8bit to quoted-printable by edgeum3.it.mcgill.ca id 4119QNcN111952 Dear Colleague, I cordially invite you to contribute a full research article to the=20 Special Issue titled "*Pattern recognition in multimodal information=20 analysis: observation, extraction, classification, and interpretation*"=20 for *Pattern Recognition Letters*. Best regards, Daniele Salvati -------------------------------------------------------------------- /Guest Editor/ daniele.salvati@xxxxxxxx https://users.dimi.uniud.it/~daniele.salvati// /-------------------------------------------------------------------- Pattern recognition in multimodal information analysis: observation, extraction, classification, and interpretation <https://www.sciencedirect.com/journal/pattern-recognition-letters/abou= t/call-for-papers#pattern-recognition-in-multimodal-information-analysis-= observation-extraction-classification-and-interpretation> In the information age, we grapple with a flood of diverse data types=20 like text, images, audio, and video. AI's strides in single-modal=20 analysis are notable, but the challenge lies in efficiently handling=20 massive multimodal data to enhance machines' understanding of the world=20 through pattern recognition. Advancements, in this area have led to=20 techniques. For example, the use of image matching in scenarios=20 involving modes is crucial in diagnostics, remote sensing, and computer=20 vision. Coordinating the retrieval of data from modes improves the=20 accuracy of pattern recognition while integrating audio video data=20 enhances speech recognition and strengthens accident monitoring=20 capabilities. In other words, multimodal learning and representation=20 yield convincingly better results with confidence. However, there are=20 still challenges that need to be addressed, such as handling types of=20 data transforming data effectively enhancing datasets and ensuring=20 interpretability of models, for processing data. In this context, this special issue outlines recent advances in the=20 pattern recognition field, intending to bring together the work of=20 scholars in this multidisciplinary subject, drawing on the different=20 skills and knowledge of pattern recognition approaches applied in the=20 multimodal information analyzing from the perspective of observing,=20 extraction, classifying and interpretation. *Topics of interest* * Multimodal recognition and learning applications * AI-enabled multimedia and multimodal applications * AI-based multimodal detection, retrieval, fusion, analysis, and recommendation * Multimodal information cooperative processing and recognition * Recognition, classification, and analysis of multimodal information * Deep learning approaches for pattern recognition in multimodal information analysis * Unsupervised/self-supervised approaches in modality alignment * Novel multimodal representation models for image (RGB-D, RGB-T) and video domains * Feature extraction, fusion, and observation of cross-modal informatio= n * Promotion of single-modal information recognition through multimodal information fusion * Multimodal representation learning algorithm based on AI and PR *Guest editors:* *Jingsha He, PhD *Beijing University of Technology, Beijing, China *Danilo Avola, PhD* Sapienza University of Rome, Roma, Italy *KC Santosh, PhD* University of South Dakota, Vermillion, USA *Mario Molinara, PhD* University of Cassino and Southern Lazio, Cassino, Italy *Daniele Salvati, PhD* University of Udine, Udine, Italy *Manuscript submission information:* The PRL's submission system (Editorial Manager=C2=AE=20 <https://www.editorialmanager.com/prletters/default2.aspx>) will be open=20 for submissions to our Special Issue from September 1st, 2024. When=20 submitting your manuscript please select the article type *VSI:PRMIA*.=20 Both the Guide for Authors and the submission portal could be found on=20 the Journal Homepage: Guide for authors - Pattern Recognition Letters -=20 ISSN 0167-8655 | ScienceDirect.com by Elsevier=20 <https://www.sciencedirect.com/journal/pattern-recognition-letters/publis= h/guide-for-authors>. The submissions should be original and technically sound, and they=20 should not have been published previously, nor be under consideration=20 for publication elsewhere. If the submissions are extended works of=20 previously published papers, the original works should be quoted in the=20 References and a description of the changes that have been made should=20 be provided. *Important dates * Submission Portal Open: September 1st, 2024 Submission Deadline: September 20th, 2024 Acceptance Deadline: December 15th, 2024 *Keywords:* Multimodal recognition; Pattern recognition; Multimodal information=20 analyzing; Data transforming; Interpretability of models. Learn more about the benefits of publishing in a special issue=20 <https://www.elsevier.com/authors/submit-your-paper/special-issues>. --------------dZl3lXV6so0lMYLNwG2tNqB4 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable X-MIME-Autoconverted: from 8bit to quoted-printable by edgeum3.it.mcgill.ca id 4119QNcN111952 <!DOCTYPE html><html><head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Dutf-8"> </head> <body> Dear Colleague,<br> <br> I cordially invite you to contribute a full research article to the Special Issue titled "<b>Pattern recognition in multimodal information analysis: observation, extraction, classification, and interpretation</b>" for <b>Pattern Recognition Letters</b>.<br= > <br> Best regards,<br> <br> Daniele Salvati<br> --------------------------------------------------------------------<= br> <font size=3D"2"><i>Guest Editor</i><br> </font><font size=3D"2"><a class=3D"moz-txt-link-abbreviated moz-txt-= link-freetext" href=3D"mailto:daniele.salvati@xxxxxxxx">daniele.salvati@xxxxxxxx= niud.it</a><br> <a class=3D"moz-txt-link-freetext" href=3D"https://users.dimi.uniud= .it/~daniele.salvati/">https://users.dimi.uniud.it/~daniele.salvati/</a><= i><br> </i></font>--------------------------------------------------------= ------------ <h1><a href=3D"https://www.sciencedirect.com/journal/pattern-recognit= ion-letters/about/call-for-papers#pattern-recognition-in-multimodal-infor= mation-analysis-observation-extraction-classification-and-interpretation"= >Pattern recognition in multimodal information analysis: observation, extraction, classification, and interpretation</a></h1> <p>In the information age, we grapple with a flood of diverse data types like text, images, audio, and video. AI's strides in single-modal analysis are notable, but the challenge lies in efficiently handling massive multimodal data to enhance machines' understanding of the world through pattern recognition. Advancements, in this area have led to techniques. For example, the use of image matching in scenarios involving modes is crucial in diagnostics, remote sensing, and computer vision. Coordinating the retrieval of data from modes improves the accuracy of pattern recognition while integrating audio video data enhances speech recognition and strengthens accident monitoring capabilities. In other words, multimodal learning and representation yield convincingly better results with confidence. However, there are still challenges that need to be addressed, such as handling types of data transforming data effectively enhancing datasets and ensuring interpretability of models, for processing data.</p> <p>In this context, this special issue outlines recent advances in the pattern recognition field, intending to bring together the work of scholars in this multidisciplinary subject, drawing on the different skills and knowledge of pattern recognition approaches applied in the multimodal information analyzing from the perspective of observing, extraction, classifying and interpretation.</p> <p><strong>Topics of interest</strong></p> <ul> <li>Multimodal recognition and learning applications</li> <li>AI-enabled multimedia and multimodal applications</li> <li>AI-based multimodal detection, retrieval, fusion, analysis, and recommendation</li> <li>Multimodal information cooperative processing and recognition</= li> <li>Recognition, classification, and analysis of multimodal information</li> <li>Deep learning approaches for pattern recognition in multimodal information analysis</li> <li>Unsupervised/self-supervised approaches in modality alignment</= li> <li>Novel multimodal representation models for image (RGB-D, RGB-T) and video domains</li> <li>Feature extraction, fusion, and observation of cross-modal information</li> <li>Promotion of single-modal information recognition through multimodal information fusion</li> <li>Multimodal representation learning algorithm based on AI and PR</li> </ul> <p><strong>Guest editors:</strong></p> <p><strong>Jingsha He, PhD<br> </strong>Beijing University of Technology, Beijing, China<br> </p> <p><strong>Danilo Avola, PhD</strong><br> Sapienza University of Rome, Roma, Italy<br> </p> <p><strong>KC Santosh, PhD</strong><br> University of South Dakota, Vermillion, USA<br> </p> <p><strong>Mario Molinara, PhD</strong><br> University of Cassino and Southern Lazio, Cassino, Italy<br> </p> <p><strong>Daniele Salvati, PhD</strong><br> University of Udine, Udine, Italy<br> </p> <p><strong>Manuscript submission information:</strong></p> <p>The PRL's submission system (<a href=3D"https://www.editorialmanag= er.com/prletters/default2.aspx">Editorial Manager=C2=AE</a>) will be open for submissions to our Special Is= sue from September 1st, 2024. When submitting your manuscript please select the article type <strong>VSI:PRMIA</strong>. Both the Guide for Authors and the submission portal could be found on the Journal Homepage: <a href=3D"https://www.sciencedirect.com/journal/= pattern-recognition-letters/publish/guide-for-authors">Guide for authors - Pattern Recognition Letters - ISSN 0167-8655 | ScienceDirect.com by Elsevier</a>.</p> <p>The submissions should be original and technically sound, and they should not have been published previously, nor be under consideration for publication elsewhere. If the submissions are extended works of previously published papers, the original works should be quoted in the References and a description of the changes that have been made should be provided.</p> <p><strong>Important dates </strong></p> <p>Submission Portal Open: September 1st, 2024</p> <p>Submission Deadline: September 20th, 2024</p> <p>Acceptance Deadline: December 15th, 2024</p> <p><strong>Keywords:</strong></p> <p>Multimodal recognition; Pattern recognition; Multimodal information analyzing; Data transforming; Interpretability of models.</p> <p><a href=3D"https://www.elsevier.com/authors/submit-your-paper/spec= ial-issues">Learn more about the benefits of publishing in a special issue</a>.</p> </body> </html> --------------dZl3lXV6so0lMYLNwG2tNqB4--