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DMNNDL 2024 : 2024 2nd International Conference on Data Mining, Neural Networks and Deep Learning | |||||||||||
Link: http://www.dmnndl.net/ | |||||||||||
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Call For Papers | |||||||||||
2024 2nd International Conference on Data Mining, Neural Networks and Deep Learning (DMNNDL 2024)
Website: http://www.dmnndl.net/ Venue: Chengdu China (both online and in-person) Conference Date: Oct. 25-27, 2024 2024 International Conference on Data Mining, Neural Networks and Deep Learning (DMNNDL 2024) will be held in Chengdu, China during Oct. 25-27, 2024. It is sponsored by The International Society for Applied Computing (ISAC) and The Technical Institute for Engineers (T.I.E.). During the upcoming conference, the invited renowned professors will share with us the recent innovations in the fields of Data Mining, Neural Networks and Deep Learning. The conference will mainly feature on keynote speeches as well as peer-reviewed paper presentations. In addition, social program or academic visit will be arranged to encourage communication, discussion or cooperation among the researchers in this field. We invite submissions of papers presenting an original high-quality research and development for the conference. All papers must be written in English and will be peer-reviewed by technical committees of the Conference and all accepted papers will be published in the conference proceedings. *Conference Speakers: Keynote Speaker I: Prof. Kaushik Rajashekara, University of Houston, USA (IEEE Fellow) Keynote Speaker II: Prof. Udaya K. Madawala, The University of Auckland, New Zealand (IEEE Fellow) Keynote Speaker III: Prof. Robert Minasian, The University of Sydney, Australia (IEEE Life Fellow) Keynote Speaker IV: Prof. Qinghe Du, Xi'an Jiaotong University, China *Call for papers: Data processing Image data mining Agent-based data mining Human, domain, organizational and social factors in data mining Scalable data preprocessing Convolutional neural networks Hebbian theory Long short term memory Residual neural networks Self-organizing feature maps Biological neural networks Neuro-Fuzzy Algorithms Evolutionary Methods Convolutional Neural Networks (CNN) Deep Hierarchical Networks (DHN) Unsupervised Feature Learning Deep Boltzmann Machines Generative Adversarial Networks (GAN) (for more topics: http://www.dmnndl.net/Call%20for%20Papers.html ) *Publication and indexing: ★DMNNDL 2024 all accepted papers will be published by ACM (ISBN: 979-8-4007-1019-3), which will be archived in the ACM Digital Library, and indexed by Ei Compendex and Scopus. ★DMNNDL 2023 conference proceedings have been published by ACM (ISBN: 979-8-4007-0762-9) and indexed by EI Compendex and Scopus successfully about 1 month after publication. *Submission Methods: 1. Online Submission System: https://cmt3.research.microsoft.com/DMNNDL2024 2. Submission Email: dmnndl@163.com Submission guidelines: http://www.dmnndl.net/Submission%20Guidelines.html *Join the conference as: Authors: Authors are expected to submit full papers to the submission system for further review by our Technical Committees. All accepted papers after proper registration and presentation in the conference will be published and submitted for indexing. Presenters Only: The presenters are expected to submit abstracts only for presentation in the conference without paper publication in the conference proceedings. Listeners: Listeners are expected to attend the conference without paper presentation or publication. Reviewers: PhD-holders in the research fields of Data Mining, Neural Networks and Deep Learning are welcome to be our reviewers and a certificate can be issued. Sponsors/Partners: If you are interested in cooperating with us, such as sponsoring or being a partner of DMNNDL 2024, you are welcome to contact us at: dmnndl@163.com *Contact us: Website: http://www.dmnndl.net/ Conference Secretary: Ms. Grace Lee Tel: (+852) 6359 2147 Email: dmnndl@163.com If you have any question or request about our conference, no matter regarding submission, registration, participation or any further question, please send email to us and you will get feedback within 24 hours. |
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