会议信息

MMLDS 2026: International Conference on Multimodality, Machine Learning and Data Science

请登录查看会议网址
免费注册:查看官网链接、跟踪截稿日期,并接收邮件提醒。
嵌入截止倒计时徽章
MMLDS
用 API 获取这条数据
搜索与榜单列表完全无需凭证;本页的完整详情需要一把免费 API 密钥。详见开发者接入页。
截稿日期:
2026-10-16 还有 20 天
通知日期:
会议日期:
2026-10-30
会议地点:
Zhengzhou, China
届数:
1
浏览: 1063   关注: 0   参加: 0

会伴指数 (CP-I)

38.1 / 100
全站第 5,406 名 / 共 5,687 个会议 · 前 96%

数据挖掘与数据库 第 327 / 337 人工智能与机器学习 第 702 / 741

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
16
资料公开度 (15%)
35

用到的输入: 有据可查的届次:1 · 过去 24 个月打开过本页的研究者:8 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后,可直接在这一页补上;分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据,而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-25

征稿

MMLDS 2026 (International Conference on Multimodality, Machine Learning and Data Science) is an academic conference held in Zhengzhou, China on 2026-10-30. The paper submission deadline is 2026-10-16.

About ICDLA 2026 In an era where information technology is advancing at an unprecedented pace, data has emerged as the cornerstone of societal progress and scientific discovery. However, the capacity of single-modality data—such as plain text or static images—to convey complex information is increasingly approaching its limits. The next paradigm shift in artificial intelligence is widely seen to lie in the deep integration and cross-disciplinary innovation of multimodal learning, machine learning, and data science. To convene global expertise in exploring the future of this interdisciplinary domain, the 2026 International Conference on Multimodality, Machine Learning and Data Science(MMLDS 2026) will be held in Zhengzhou, China, from October 30 to November 1, 2026. This conference aims to establish an international platform for scholars, engineers, and industry leaders worldwide to engage in in-depth discussions on core topics, including multimodal perception and understanding, machine learning theory and methodologies, data science and intelligent systems, and cutting-edge applications. The topics of interest for submission include, but are not limited to: ◕Track1: Multimodal Learning & Artificial Intelligence Image Understanding Video Analysis Speech Recognition & Processing Text & Language Modeling Cross-Modal Retrieval Multimodal Fusion Techniques Affective Computing & Cognitive Analysis Medical Image Analysis Natural Language Processing Generative Models Intelligent Human-Computer Interaction Intelligent Recommendation Systems Autonomous Driving & Perception Visual Question Answering Modality Transformation & Synthesis ◕Track2: Data Science & Big Data Analytics Data Preprocessing & Cleaning Data Mining Techniques Big Data Management Data Visualization Data Integration & Modeling Data-Driven Decision Making Spatiotemporal Data Analysis Network Data Analysis Social Computing & Behavioral Analysis Business Intelligence Data Security & Privacy Cloud Computing & Data Processing High-Performance Data Analytics Data Science Methodology Data-Driven Scientific Research ◕Track3: Machine Learning & Deep Learning Supervised Learning Unsupervised Learning Reinforcement Learning Self-Supervised Learning Deep Neural Networks Graph Neural Networks Sequence Modeling Model Compression & Optimization Transfer Learning Federated Learning Explainable AI Anomaly Detection Time Series Prediction Model Evaluation & Selection Automated Machine Learning (AutoML) Publication All accepted full papers will be published in the conference proceedings and will be submitted to EI Compendex / Scopus for indexing.
由 Dou Sun 最后更新于

相关期刊

CCF全称影响因子出版商ISSN
BMachine Learning2.9Springer0885-6125
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

评论 0

暂无评论。

请登录后发表评论