About to MSIP 2027
This conference will be held in Dongguan to create a growth oriented communication platform for young researchers, focusing on three core directions: innovation in small sample machine learning algorithms, development of lightweight end-to-end intelligent systems, and breakthroughs in multimodal information processing technology. The conference sets up a dedicated reporting track for young scholars and a one-on-one guidance workshop for internationally renowned scholars, focusing on cutting-edge topics such as industrial quality inspection small sample model training, low-power optimization of edge intelligent systems, and efficient integration of multi-source heterogeneous industrial information. It provides a direct channel for young researchers to showcase their achievements and connect resources, and helps young technical talents in the field of intelligent manufacturing in the Pearl River Delta to grow rapidly.
IMPORTANT DATES
2027-02-12-Submission Deadline
2027-02-19-Registration Deadline
2027-02-27-Conference Date
About a week after the submission-Notification Date
RECORD
All full paper submissions to the MSIP 2027 could be written in English and will be sent to at least two reviewers and evaluated based on originality, technical or research content or depth, correctness, relevance to conference, contributions, and readability. All accepted papers of MSIP 2027 will be published in the conference proceedings, which will be submitted to EI Compendex, Scopus for indexing.
Paper template
Please refer to the paper template for layout
Click to download
Register
All attendees must register in advance to attend the meeting
Consulting service
Submit
Please submit the full text/abstract of the paper to us through the electronic submission system
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Call For Papers
Machine Learning
Basic Theory and Algorithms of Machine Learning
Supervised Learning and Unsupervised Learning
Reinforcement Learning and Transfer Learning
Federated Learning and Privacy Protection
Standardization of Machine Learning
Machine Learning Education
Future Development Trends of Machine Learning
Machine Learning and Artificial Intelligence
Machine Learning and Big Data
Machine Learning and Cloud Computing
Machine Learning and the Internet of Things
Machine Learning and Environmental Protection
Machine Learning and Industrial Applications
Machine Learning and Agricultural Applications
Machine Learning and Forestry Applications
Machine Learning and Fishery Applications
Machine Learning and Animal Husbandry Applications
......
Indexing Service
Technical Sponsor
Call for Reviewers
As a platform for global academic communication, the quality of conference publication has always an aspect attracting much of our attention. To ensure quality of our publication and to better serve the peers in academic circle, we now call for reviewers among professionals and experts of the world. Professionals and experts who hold PhD (doctoral) degree in the conference related areas are encouraged to join in us and together, we will work hard to become a world-class academic conference. Please send us your CV by email (msip@confsflow.com) if you are interested in it.
SCI Journal
Contributors are encouraged to submit papers / abstracts to the conference. The organizing committee will select high-quality papers and recommend them to SCI/SSCI journals. For specific matters, please contact the person in charge of the conferrence.
Submission Guidelines
Delegates are encouraged to submit their papers/abstracts to the conference. Good quality papers will be selected by the organizing committee and Prof. Soteris Kalogirou, the editor in chief. After it, the authors will be invited to extent their papers/abstracts and submit them to msip@confsflow.com. The normal size of research papers is 4,000-6,000 words excluding abstract and references.
Submission Portal
If you have any questions or need any help about the conference, please feel free to contact our conference experts on the right:
李老师
TEL:185 8152 0396
QQ:3959598883
E-mail:msip@confsflow.com
About Plagiarism Check
Crosscheck Powered by iThenticate will be used for plagiarism check. The amount of duplication from previously published content should be less than 20%; If the amount of duplication is 20% - 35%, modification maybe required; if the amount of duplication exceeds 35%, the article will be rejected. Please note that there will be no refund for no-shows.