*The 2nd International Conference on Machine Learning and Pattern Recognition (MLPR 2024)* When: August 2-4, 2024 Where: Osaka, Japan Website: http://www.mlpr.org/ The 2nd International Conference on Machine Learning and Pattern Recognition (MLPR 2024) will be held in Osaka, Japan during August 2-4, 2024. MLPR 2024 is organized by Ritsumeikan University, Japan. The conference includes keynote talks, invited talks, forums and oral and poster presentations of author papers. We invite submissions of papers on all topics related to machine learning and pattern recognition for the main conference proceedings. All papers will be reviewed in a double-blind process and accepted papers will be presented at the conference. ==Keynote & Invited Speakers== Prof. Hiroyuki Kudo, University of Tsukuba, Japan; Prof. Ce Zhu (IEEE Fellow), University of Electronic Science and Technology of China, China; Prof. Amir Hussain, Edinburgh Napier University, UK; Prof. Yen-Wei Chen, Ritsumeikan University, Japan; Assoc. Prof. Guangyu Gao, Beijing Institute of Technology, China; Assoc. Prof. Porawat Visutsak, King Mongkut’s University of Technology North Bangkok, Thailand; Assoc. Prof. Zheng-Ming Gao, Jingchu University of Technology, China; Prof. Jiarong Yang, Shanghai Electric Group Co., Ltd., Central Academe, China. ==Conference Proceedings== Submitted papers will be peer reviewed by conference committees, and accepted papers after proper registration and presentation will be published in the International Conference Proceedings Series by ACM (ISBN: 979-8-4007-1000-1), which will be submitted for indexing by Ei Compendex, Scopus, etc. ==Call for Paper== Track 1: Machine Learning ▪ Active learning ▪ Dimensionality reduction ▪ Feature selection ▪ Graphical models ▪ Imitation learning ▪ Intelligent Business Computing ▪ Intelligent Systems ▪ Intelligent control system ▪ Intelligent human machine interface ▪ Intelligent robot ▪ Latent variable models ▪ Learning for big data ▪ Learning from noisy supervision ▪ Learning in graphs ▪ Multi-objective learning ▪ Multiple instance learning ▪ Multi-task learning Track 2: Pattern Recognition ▪ Analysis and detection of singularities ▪ Animation image analysis ▪ Classification ▪ Cluster analysis ▪ Deformation analysis ▪ Descriptor of shapes ▪ Diagnosis of faults ▪ Document analysis ▪ Emotion computation ▪ Enhancement and restoration ▪ Feature extraction ▪ Hand gestures classification ▪ Human face recognition ▪ Image compression ▪ Image fusion ▪ Image indexing and retrieval ▪ Image recovery For more topics, please check: http://www.mlpr.org/cfp.html ==Submission Guideline== #Submission Requirements# 1). Language English is the official language of the conference; the paper should be written and presented only in English. 2). Submission Type * Abstract submission for presentation only without publication. * Full paper submission for both presentation and publication. 3). Paper Length Full Paper should be no less than 4 full pages in two columns. Any manuscript of more than 5 pages will be charged for pages exceeding the limit. 4). Papers submitted to the conference should report original, previously unpublished research results, experiments or theories and must not be under consideration for publication elsewhere. #Submission Process# 1). Download the Paper Template for formatting your paper. 2). Submit your paper to Online Submission System (http://confsys.iconf.org/submission/mlpr2024) or mlpr_Conf@outlook.com. - via online submission system: an account is needed, if you don't have, please register first. - via mailbox: the email subject should be named as "Submission-MLPR 2024-Full Paper/ Abstract" 3). The conference secretary (mlpr_Conf@outlook.com) will contact you within three working days once receiving your submission. ==Contact== The secretary of MLPR 2024 will collect your paper contributions and respond to your queries. If you have any questions, please feel free to contact the conference secretary. Conference Secretary: Miss Chloe Jiang Email: mlpr_Conf@outlook.com Tel.: +86-19180927671 WeChat: csit2009 Office Hour: Mon. - Fri. 9:30-18:00 (GMT+8 Time Zone)