日本データベース学会の皆様
#重複してお受け取りの場合はご容赦ください
岩手大学の張 建偉と申します。
お世話になっております。
国際会議 MIPR 2026 (The 9th IEEE International Conference on Multimedia
Information Processing and Retrieval)
の投稿締切が迫っておりますので、最終案内として共有させていただきます。
■ 投稿締切:4/30 (AoE)
本会議では、完成度の高い研究成果に加え、手頃ですぐに投稿できる成果も広く歓迎されています。
短期間でまとめられる内容でも投稿をご検討いただけますと幸いです。
マルチメディア情報処理・検索、生成AI、マルチモーダル学習など幅広いトピックが対象です。
▼ 詳細・投稿はこちら
https://mipr2026.org/index.html
締切間近となっておりますので、ぜひこの機会にご投稿をご検討ください。
どうぞよろしくお願いいたします。
==========================
IEEE MIPR 2026 -- Call for Papers
Bangkok, Thailand, August 9–11, 2026
==========================
With vast amounts of multimedia data now widely accessible,
understanding spatial and/or temporal phenomena has become essential for
numerous applications, driving the need for advanced techniques in
processing, analyzing, searching, mining, and managing such data.
The 9th IEEE International Conference on Multimedia Information
Processing and Retrieval (IEEE MIPR 2026) will be held in Bangkok,
Thailand, 9–11 August 2026. It offers a premier forum for presenting
original research and practical advances in the design, implementation,
and application of multimedia information processing and retrieval. The
congress convenes university researchers, scientists, industry
professionals, software engineers, and graduate students for a four-day
program that blends a flagship technical track with keynote speeches,
workshops, demonstrations, posters, tutorials, and panels.
The Organizing Committee members of the conference look forward to
welcoming you in person in Bangkok in August 2026.
1 Important Dates
==========================
All deadlines below are 11:59 PM Anywhere on Earth
- Submission deadline: April 30, 2026
- Acceptance Notifications: May 31, 2026
- Camera Read Deadline: June 17, 2026
2 Paper Submission
==========================
Papers reporting original and unpublished research results pertaining to
the topics in the CFP are solicited. Full paper manuscripts must be in
English, following the IEEE two-column template instructions.
Submissions should include the title, author(s), affiliation(s), e-mail
address(es), abstract, and institution information in the first page.
The online submission site is https://cmt3.research.microsoft.com/MIPR2026.
We invite submissions in three categories: regular paper (6 pages), demo
paper (4 pages) and poster paper (2 pages). Each submission will undergo
a thorough peer-review process.
3. Research Track Topics:
==========================
Generative and Foundation Models in Multimedia
• AI-generated Media
• Foundation Models in Vision and Audio
• Media Generation with Generative Models
• Media Generation with Large Vision/Language Models
• Visual and Vision-Language Pre-training
• Generic Vision Interface
• Alignments in Text-to-image Generation
• Large Multimodal Models
• Multimodal Agents
Trustworthy AI in Multimedia
• AI Reliability for Multimedia Applications and Systems
• AI Fairness for Multimedia Applications and Systems
• AI Robustness for Multimedia Applications and Systems
• Attack and Defense for Multimedia Applications and Systems
• Security of Large AI Models
Audio and Speech in Multimedia
• Speech/Voice Synthesis
• Analysis of Conversation
• Speaker and Language Identification
• Audio Signal Analysis
• Spoken Language Generation
• Automatic Speech Recognition
• Spoken Dialogue and Conversational AI Systems
Content Understanding
• Multimedia Telepresence and Virtual/Augmented/Mixed Reality
• Visual Concept Detection
• Detection and Tracking
• 3D Modeling, Reconstruction, and Interactive Applications
• Multimodal/Multisensory Interfaces, Integration, and Analysis
• Effective and Scalable Solution for Big Data Integration
• Affective and Perceptual Multimedia
Multimedia Retrieval
• Multimedia Search and Recommendation
• Web-Scale Retrieval
• Relevance Feedback, Active/Transfer Learning
• 3D and Sensor Data Retrieval
• Multimodal Media (Images, Videos, Audio, Texts, Graph/Relationship)
Retrieval
• High-Level Semantic Multimedia Features
Machine/Deep Learning/Data Mining
• Deep Learning in Multimedia Data and Multimodal Fusion
• Deep Cross-Learning for Novel Features and Feature Selection
• High-Performance Deep Learning (Theories and Infrastructures)
• Spatio-Temporal Data Mining
• Novel Dataset for Learning and Multimedia
Multimedia Systems and Infrastructures
• Multimedia Systems and Middleware
• Software Infrastructure for Data Analytics
• Distributed Multimedia Systems and Cloud Computing
• Internet Scale System Design
• Information Coding for Content Delivery
• Real-Time Data Processing for Internet of Multimedia Things
Data Management
• Multimedia Data Collection, Modeling, Indexing, or Storage
• Multimedia and Content Forensics
• Data Integrity, Security, Protection, and Privacy
• Standards and Policies for Data Management
• Steganography for Secure Data Embedding
• Homomorphic Encryption for Secure Data Processing
Applications
• Multimedia Applications for Health and Sports
• Multimedia Applications for Culture and Education
• Multimedia Applications for Fashion and Living
• Multimedia Applications for Security and Safety
• Multimedia Applications for Agriculture
• Autonomous Systems (Self-driving Cars, Robots, Drones, etc.)
• Mobile and Wearable Multimedia
4. Bonus
==========================
Top quality papers after presented in the conference will be recommended
for extension and publication in several international journals, e.g.,
IEEE Transactions on Multimedia (TMM), ACM Transactions on Multimedia
Computing Communications and Applications (TOMM), IEEE MultiMedia
Magazine, EURASIP Journal on Image and Video Processing (EURASIP JIVP),
Human-Centric Intelligent Systems, etc.
日本データベース学会の皆様
お茶大のLeです。
2026年8月9日〜11日にタイで開催される MIPR 2026 の最終 CFP のご案内です。締切は 4月30日 AoE です。
すぐに投稿可能な研究成果がありましたら、ぜひ投稿をご検討ください。
よろしくお願いします。
Le
==========================
IEEE MIPR 2026 -- Call for Papers
Bangkok, Thailand, August 9–11, 2026
==========================
With vast amounts of multimedia data now widely accessible, understanding spatial and/or temporal phenomena has become essential for numerous applications, driving the need for advanced techniques in processing, analyzing, searching, mining, and managing such data.
The 9th IEEE International Conference on Multimedia Information Processing and Retrieval (IEEE MIPR 2026) will be held in Bangkok, Thailand, 9–11 August 2026. It offers a premier forum for presenting original research and practical advances in the design, implementation, and application of multimedia information processing and retrieval. The congress convenes university researchers, scientists, industry professionals, software engineers, and graduate students for a four-day program that blends a flagship technical track with keynote speeches, workshops, demonstrations, posters, tutorials, and panels.
The Organizing Committee members of the conference look forward to welcoming you in person in Bangkok in August 2026.
1 Important Dates
==========================
All deadlines below are 11:59 PM Anywhere on Earth
- Submission deadline: April 30, 2026
- Acceptance Notifications: May 31, 2026
- Camera Read Deadline: June 17, 2026
2 Paper Submission
==========================
Papers reporting original and unpublished research results pertaining to the topics in the CFP are solicited. Full paper manuscripts must be in English, following the IEEE two-column template instructions. Submissions should include the title, author(s), affiliation(s), e-mail address(es), abstract, and institution information in the first page.
The online submission site is https://cmt3.research.microsoft.com/MIPR2026.
We invite submissions in three categories: regular paper (6 pages), demo paper (4 pages) and poster paper (2 pages). Each submission will undergo a thorough peer-review process.
3. Research Track Topics:
==========================
Generative and Foundation Models in Multimedia
• AI-generated Media
• Foundation Models in Vision and Audio
• Media Generation with Generative Models
• Media Generation with Large Vision/Language Models
• Visual and Vision-Language Pre-training
• Generic Vision Interface
• Alignments in Text-to-image Generation
• Large Multimodal Models
• Multimodal Agents
Trustworthy AI in Multimedia
• AI Reliability for Multimedia Applications and Systems
• AI Fairness for Multimedia Applications and Systems
• AI Robustness for Multimedia Applications and Systems
• Attack and Defense for Multimedia Applications and Systems
• Security of Large AI Models
Audio and Speech in Multimedia
• Speech/Voice Synthesis
• Analysis of Conversation
• Speaker and Language Identification
• Audio Signal Analysis
• Spoken Language Generation
• Automatic Speech Recognition
• Spoken Dialogue and Conversational AI Systems
Content Understanding
• Multimedia Telepresence and Virtual/Augmented/Mixed Reality
• Visual Concept Detection
• Detection and Tracking
• 3D Modeling, Reconstruction, and Interactive Applications
• Multimodal/Multisensory Interfaces, Integration, and Analysis
• Effective and Scalable Solution for Big Data Integration
• Affective and Perceptual Multimedia
Multimedia Retrieval
• Multimedia Search and Recommendation
• Web-Scale Retrieval
• Relevance Feedback, Active/Transfer Learning
• 3D and Sensor Data Retrieval
• Multimodal Media (Images, Videos, Audio, Texts, Graph/Relationship) Retrieval
• High-Level Semantic Multimedia Features
Machine/Deep Learning/Data Mining
• Deep Learning in Multimedia Data and Multimodal Fusion
• Deep Cross-Learning for Novel Features and Feature Selection
• High-Performance Deep Learning (Theories and Infrastructures)
• Spatio-Temporal Data Mining
• Novel Dataset for Learning and Multimedia
Multimedia Systems and Infrastructures
• Multimedia Systems and Middleware
• Software Infrastructure for Data Analytics
• Distributed Multimedia Systems and Cloud Computing
• Internet Scale System Design
• Information Coding for Content Delivery
• Real-Time Data Processing for Internet of Multimedia Things
Data Management
• Multimedia Data Collection, Modeling, Indexing, or Storage
• Multimedia and Content Forensics
• Data Integrity, Security, Protection, and Privacy
• Standards and Policies for Data Management
• Steganography for Secure Data Embedding
• Homomorphic Encryption for Secure Data Processing
Applications
• Multimedia Applications for Health and Sports
• Multimedia Applications for Culture and Education
• Multimedia Applications for Fashion and Living
• Multimedia Applications for Security and Safety
• Multimedia Applications for Agriculture
• Autonomous Systems (Self-driving Cars, Robots, Drones, etc.)
• Mobile and Wearable Multimedia
4. Bonus
==========================
Top quality papers after presented in the conference will be recommended for extension and publication in several international journals, e.g., IEEE Transactions on Multimedia (TMM), ACM Transactions on Multimedia Computing Communications and Applications (TOMM), IEEE MultiMedia Magazine, EURASIP Journal on Image and Video Processing (EURASIP JIVP), Human-Centric Intelligent Systems, etc.
日本データベース学会の皆様
京都工芸繊維大学のDuanです。
2026年11月13日〜15日に香港で開催されるデータマイニングに関する国際会議ADMA2026におけるSpecial Session "Educational Data Mining in the Era of Large Language Models (EDM-LLM)" につきまして、ご案内申し上げます。
ぜひ投稿をご検討いただければ幸いです。
何卒よろしくお願い申し上げます。
+++ General Information +++
The 22nd International Conference on Advanced Data Mining and Applications 2026
Special Session: Educational Data Mining in the Era of Large Language Models (EDM-LLM)
13th ~ 15th November, 2026
Hong Kong
https://adma2026.github.io/
+++ Important Dates +++
- Full/Poster Paper submission: June 26, 2026
- Acceptance notification: August 21, 2026
- Camera-ready papers submission: September 4, 2026
- Conference Dates: November 13-15, 2026
+++ Aims and Scope +++
Educational Data Mining lies at the intersection of data mining, machine learning, the learning sciences, and educational technology. This special session aims to provide a focused forum within ADMA2026 for research on how advanced data mining methods can be used to understand learning processes, support teachers and learners, personalize instruction, and examine the growing role of large language models in educational settings. The session welcomes methodological papers, application papers, benchmark studies, system papers, and reports of industrial practice. It is intended both for work that uses educational data to motivate advances in data mining and for work that applies state of-the-art data mining methods to important educational problems. In particular, the session aims to connect the broader data mining community with real educational challenges involving sequential, relational, textual, code-based, and multimodal data.
+++ Topics +++
The special session will cover, but are not limited to:
- Learner knowledge and performance modeling, knowledge tracing, mastery estimation, and academic risk prediction;
- Domain knowledge modeling, prerequisite discovery, knowledge component discovery, and graph/sequence mining of learning processes;
- Educational recommenders, instructional sequencing, intervention optimization, and reinforcement learning for adaptive learning;
- Multimodal learning analytics using logs, text, code, speech, video, eye-tracking, or classroom interaction data;
- Social and collaborative learning analytics, peer learning, discussion/forum mining, and group interaction modeling;
- Open-ended assessment, automated grading, writing and code analytics, peer review modeling, and educational feedback generation;
- LLM applications in EDM, including intelligent tutoring, hint generation, question generation, feedback synthesis, knowledge component extraction, item difficulty estimation, and classroom support;
- Evaluation of LLMs in education, human-AI comparison, benchmarking against student performance, and studies of AI-assisted learning behaviors;
- Data resources, benchmarks, and cross-platform or cross-institutional studies for educational data mining.
+++ Publication +++
Accepted papers will be published by Springer in their Lecture Notes in Artificial Intelligence (LNAI) and indexed in EI and DBLP.
+++ Submission Instructions +++
Manuscripts must be prepared in accordance with the LNAI format and should not exceed 15 pages. For the template and details on the LNAI style, please check the following website: https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu…
Papers will go through a full peer review process in a double-blind manner.
Submission site: https://cmt3.research.microsoft.com/ADMA2026
+++ Special Session Chair +++
- Weining Qian, East China Normal University, China
- Yun Liu, Kyoto Institute of Technology, Japan
- Yijun Duan, Kyoto Institute of Technology, Japan