2026 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026)
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About this event
2026 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026)
Date: September 18-20, 2026
Venue: Huaqiao University, Xiamen, Fujian, China
Address: No.668 Jimei Avenue, Xiamen, Fujian, China 361021
About AIPR 2026
The 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026) will be held from September 18-20, 2026, in Xiamen, China. Organized by Huaqiao University and co-sponsored by Fujian Cyberspace Security Association, Wuhan Institute of Technology, and Minnan Normal University, this conference builds on the success of its previous editions, including those held in Beijing, Quanzhou, and virtual platforms during the pandemic years.
AIPR 2026 aims to foster academic exchange and potential collaborations in the fields of artificial intelligence and pattern recognition. It invites experts, scholars, and researchers to submit papers and participate in this international gathering. The conference will feature various tracks, including Pattern Recognition and Machine Learning, Computer Vision and Robot Vision, and Image, Speech, Signal, and Video Processing.
Key Details
- Submission Deadline: July 15, 2026
- Notification Date: August 5, 2026
- Registration Deadline: August 10, 2026
- Camera Ready Deadline: August 10, 2026
- Conference Dates: September 18-20, 2026
Conference Tracks
- Pattern Recognition and Machine Learning
- Computer Vision and Robot Vision
- Image, Speech, Signal, and Video Processing
Publication
AIPR 2026 welcomes innovative research submissions from academia, industry, and government. Accepted papers, after proper registration and presentation, will be published in a volume of SPIE Proceedings. This volume will be included in the SPIE Digital Library and indexed by Ei Compendex, Scopus, and CPCI (Web of Science).
Participation
Participants can attend as delegates without presenting research. Registration for delegates is available through the Online Registration System. After registration, participants are requested to confirm their attendance via email.
Contact and Venue Information
For more information, please visit the official website at https://www.aipr.net/. For venue inquiries, contact the organizers at the provided email address on the website.
Data sheet
2026 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026) – Event Attendee & Buyer Profile Analysis
Event date: September 18–20, 2026
Location: Huaqiao University, Xiamen, Fujian, China
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | 2026 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026) |
| Event Date | September 18–20, 2026 |
| Event Status | Upcoming |
| Venue | Huaqiao University |
| City | Xiamen |
| State / Region | Fujian |
| Country | China |
| Organizer | Huaqiao University |
| Official Event Website | aipr.net |
| Event Type | International academic conference / research and technical paper presentation event |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Global, with strong China-based host concentration and international academic participation intent |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for headcount; organizer confirms event scope, dates, venue, tracks, organizer, co-sponsors, and publication route. |
| Main Purpose of Event | Academic exchange, research publication, technical networking, and collaboration development in artificial intelligence and pattern recognition. |
About the Event
AIPR 2026 is the ninth edition of an international conference focused on artificial intelligence and pattern recognition. The official event website confirms that the conference will take place in Xiamen, China, from September 18 to 20, 2026, at Huaqiao University. It is mainly organized by Huaqiao University and co-sponsored by Fujian Cyberspace Security Association, Wuhan Institute of Technology, and Minnan Normal University. Core technical tracks include Pattern Recognition and Machine Learning, Computer Vision and Robot Vision, and Image, Speech, Signal and Video Processing.
From a commercial intelligence perspective, this is primarily a research-led, paper-driven conference rather than a large trade exhibition. Its strongest value lies in identifying AI researchers, academic labs, technical committee members, university partnerships, R&D stakeholders, and selected industry or government research participants. It is relevant for organizations selling AI research tools, computer vision infrastructure, edge computing, data labeling, simulation, lab software, publication support, research collaboration services, and higher-education technology solutions. It is less suitable for pure mass-market attendee list building because the organizer does not publicly confirm a broad attendee directory or footfall volume.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University researchers and faculty | Universities, engineering schools, AI labs, pattern recognition research groups | Influence research software, compute platforms, datasets, lab tools, and collaboration decisions | High relevance for research tools, GPU infrastructure, academic software, and technical partnerships |
| PhD students and graduate researchers | Academic departments, graduate programs, supervised research teams | Technical evaluators and end users; lower direct budget authority | Useful for product trials, tool adoption, and future advocacy inside labs |
| Industry R&D and applied AI teams | AI product companies, computer vision firms, robotics teams, enterprise innovation units | Can influence software licensing, model development platforms, and integration partners | Relevant for model deployment tools, MLOps, sensors, annotation, and testing solutions |
| Government and public-sector researchers | Government research institutes, public universities, state innovation programs | Potential procurement influence for approved research projects and collaborative programs | Relevant where offerings align with public research, AI security, and national innovation priorities |
| Technical committee members and senior scholars | Senior academics and recognized experts in related fields | High influence on partnerships, reputation, referrals, and institutional introductions | Strong for relationship-led outreach and strategic collaboration |
| Conference delegates not presenting papers | Interested academics, practitioners, and institutional representatives | Moderate influence; often evaluators or network builders | Useful for awareness, partner scouting, and discovery conversations |
| Publication-oriented authors | Researchers from academia, industry and government, as confirmed by the organizer | Strong technical influence; variable purchasing authority | Best for niche technical offerings, benchmarking tools, and sponsored research engagement |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Xiamen | Host-city academics, university labs, and local technical communities | Medium | Venue is Huaqiao University in Xiamen. |
| Fujian Province | Regional university researchers, cybersecurity associations, and applied research institutions | High | Co-sponsorship by Fujian Cyberspace Security Association indicates regional network pull. |
| Major China academic and technology hubs | Researchers and AI practitioners from other Chinese cities and universities | High | Prior editions were held in Beijing, Xiamen, and Quanzhou, supporting national continuity. |
| Asia-Pacific | International researchers and delegates able to travel to China | Medium | International positioning is confirmed by the event title and English-language paper call. |
| Global | Authors and delegates from academia, industry, and government worldwide | Medium | Global reach is likely, but attendee country breakdown is not publicly confirmed. |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event is branded as an international conference, accepts submissions from academia, industry and government, and publishes accepted papers in an indexed proceedings volume. |
| National | Secondary practical reach | In practice, the strongest concentration is likely within China due to venue location, organizer base, and co-sponsor profile. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Huaqiao University | Organizer / host university / research buyer | Main organizer and conference venue; relevant for academic technology procurement, research collaboration, and lab partnerships. | hqu.edu.cn | Professor, Dean, Lab Director, Director of Research, IT Director | Confirmed Current-Year Participant |
| Fujian Cyberspace Security Association | Co-sponsor / association / ecosystem influencer | Relevant for AI security, academic-industry coordination, and regional technical network access. | Not publicly verified from supplied source text | Secretary General, Program Director, Partnerships Director, Association Manager | Confirmed Current-Year Participant |
| Wuhan Institute of Technology | Co-sponsor / university / research buyer | Confirmed co-sponsor with likely faculty and technical participation relevant to AI and pattern recognition. | wit.edu.cn | Professor, Research Director, Department Chair, IT Director | Confirmed Current-Year Participant |
| Minnan Normal University | Co-sponsor / university / research buyer | Confirmed co-sponsor and relevant institutional participant for AI-related academic collaboration. | mnnu.edu.cn | Professor, Dean, Director of Research, School Administrator | Confirmed Current-Year Participant |
| Current-year attendee organizations not publicly disclosed beyond organizer and co-sponsors | Attendee directory limitation | The official website confirms participation categories from academia, industry and government, but does not publish a full 2026 attendee or buyer organization list in the supplied source text. | aipr.net | N/A | Confirmed Government / Procurement Organization |
Note: This event does not publicly present a broad current-year attendee list in the supplied official source material. For lead generation, the most reliable immediate targets are organizer, co-sponsors, committee members, speakers, published authors, and affiliated university labs once listed by the organizer.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Professor / Principal Investigator | Research / Academic | Senior | Direct influence over research direction, tool selection, partnerships, and grant-related decisions. |
| 2 | Lab Director | Research / Engineering | Director | Likely owner of infrastructure, software, benchmarking, and external collaboration needs. |
| 3 | Director of Research | R&D | Director | Key for institutional adoption of AI platforms, datasets, and research services. |
| 4 | Dean / Associate Dean | Academic Administration | Executive | Useful for strategic partnerships, academic programs, and institutional sponsorships. |
| 5 | IT Director | Information Technology | Director | Relevant for compute environments, data storage, networking, security, and systems integration. |
| 6 | Computer Vision Engineer / Research Scientist | Engineering / R&D | Manager / Senior IC | End user and evaluator for model tooling, annotation, testing, and deployment support. |
| 7 | Program Manager | Research Programs / Innovation | Manager | Helps coordinate grants, collaborations, event participation, and vendor engagement. |
| 8 | Partnerships Director | Partnerships / External Relations | Director | Important for sponsorships, institutional cooperation, and research commercialization links. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Higher Education | Best fit for organizer, co-sponsoring universities, faculty, and research labs. | Academic software, compute infrastructure, lab tools, collaboration platforms |
| 2 | Research | Strong fit for non-university institutes and applied AI research bodies. | Research tooling, data platforms, simulation, analytics |
| 3 | Information Technology & Services | Matches applied AI solution providers and enterprise technical teams. | AI integrations, services, technical consulting |
| 4 | Computer Software | Relevant for model development tools, MLOps, data processing, and analytics vendors. | AI software licensing and developer tools |
| 5 | Computer Hardware | Relevant for edge devices, acceleration hardware, and compute environments. | GPU servers, embedded AI hardware, vision systems |
| 6 | Electrical/Electronic Manufacturing | Fits sensor, imaging, and robotics-adjacent organizations. | Sensors, imaging equipment, AI-enabled devices |
| 7 | Industrial Automation | Relevant where computer vision and machine learning are applied to manufacturing and robotics. | Vision inspection, automation intelligence, robotics |
| 8 | Government Administration | Fits public research and government innovation stakeholders mentioned by the organizer. | Public-sector AI research collaboration and approved procurement |
| 9 | Computer Networking | Relevant for research networks, data movement, and high-performance connectivity. | Campus networking, distributed compute environments |
| 10 | Computer & Network Security | Supports relevance from the Fujian Cyberspace Security Association co-sponsorship. | AI security, secure datasets, cyber research tooling |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Not Confirmed | Official website content supplied | No attendee total published in the supplied primary source. |
| Exhibitor count | Not applicable / not publicly disclosed | Not Confirmed | Official website content supplied | This appears to be a conference rather than a traditional expo floor event. |
| Buyer count | Buyer count not publicly confirmed | Not Confirmed | Official website content supplied | The event is research-focused; attendee composition is broader than formal buyer programs. |
| Speaker count | Not publicly confirmed in supplied source text | Not Confirmed | Official website content supplied | Website navigation includes a speakers section, but no speaker total was provided in the source text. |
| Sponsor count | 3 co-sponsors confirmed | Confirmed | Official website content supplied | Fujian Cyberspace Security Association, Wuhan Institute of Technology, and Minnan Normal University. |
| Historical attendance | Not publicly confirmed by the organizer in the supplied text | Historical / prior-year evidence unavailable for headcount | Official website content supplied | Only previous edition locations and publication history are confirmed in the source text. |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Artificial Intelligence | Model development, experimentation, evaluation, and publication-ready research workflows | Engage faculty, R&D teams, and technical committee members with demos and research use cases | AI platforms, model development tools, MLOps, benchmarking environments |
| Pattern Recognition and Machine Learning | Algorithms, datasets, compute, and evaluation tooling | Position solutions that accelerate experimentation and reproducibility | Dataset management, training infrastructure, experiment tracking |
| Computer Vision and Robot Vision | Image pipelines, vision models, testing, and deployment environments | Target labs and applied teams working on imaging and visual perception | Vision sensors, labeling tools, simulation, edge inference hardware |
| Image, Speech, Signal and Video Processing | Large data handling, annotation, processing pipelines, and analytics | Present workflow improvements and technical integration support | Signal processing software, storage, annotation services, analytics tools |
| Cybersecurity-adjacent AI research | Secure data handling, trustworthy AI, and cyber-informed technical collaboration | Leverage regional co-sponsor relationships and research security interests | Secure AI environments, privacy tooling, cyber analytics platforms |
| Research collaboration and publication | Credible publishing path, collaboration visibility, and technical networking | Offer partnership frameworks, grants support, or research enablement services | Collaboration platforms, academic partnerships, sponsored research programs |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Medium | Strong for academic, research, and technical solution providers; weaker for mainstream procurement-led selling. |
| Decision-maker availability | Medium | Professors, lab directors, and academic leaders are likely present, but many attendees may be researchers without final budget authority. |
| Data collection potential | Low | Public attendee and buyer data is limited. Not ideal for large-scale attendee list building from official open sources alone. |
| Apollo targeting potential | High | Good fit for account-based targeting by universities, research institutes, AI software vendors, and technical leadership roles. |
| Geographic targeting potential | High | Can be segmented by China, Fujian, Xiamen, and broader Asia-Pacific research clusters. |
| Best outreach approach | High | Use account-based outreach, speaker/author follow-up, and institutional partnership messaging rather than generic event list outreach. |
| Overall lead quality | Medium | High quality for niche AI research solutions; moderate for broader commercial demand generation. |
| Best use case | High | Best for research partnerships, AI tooling outreach, academic account targeting, and technical ecosystem mapping. |
| Limitations / risks | Medium | Limited public attendee disclosure, uncertain headcount, and fewer traditional procurement buyers than at a commercial expo. |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Higher Education; Research; Information Technology & Services; Computer Software; Computer Hardware; Industrial Automation; Electrical/Electronic Manufacturing; Government Administration; Computer & Network Security | Concentrates on the most relevant institutional and applied AI buyer environments. |
| Departments | Research; Engineering; Information Technology; Education; Program Management; Partnerships | Targets the functions most likely to engage on AI research or infrastructure discussions. |
| Seniority | Director; VP; CXO; Partner; Head; Manager; Professor-equivalent where available | Focuses on budget owners, institutional influencers, and technical leads. |
| Job titles | Professor, Principal Investigator, Lab Director, Director of Research, Dean, Associate Dean, IT Director, Research Scientist, Computer Vision Engineer, Program Manager, Partnerships Director | Builds a practical outreach list around research decision makers and evaluators. |
| Geography | China; Fujian; Xiamen; broader Asia-Pacific; selected global AI research hubs | Supports local, national, and international segmentation. |
| Employee size | 201–500; 501–1,000; 1,001–5,000; 5,001+ | Useful for universities, institutes, and mature technical organizations with defined budgets. |
| Keywords | artificial intelligence, pattern recognition, machine learning, computer vision, robot vision, signal processing, image processing, speech processing, video processing, AI lab, research center | Narrows to the conference’s confirmed technical themes. |
| Technologies, if relevant | GPU computing, machine learning frameworks, computer vision stacks, data annotation, MLOps | Improves fit for infrastructure and software vendors. |
| Revenue range, if relevant | Use selectively; not essential for university-heavy targeting | Useful mainly for private-sector AI and hardware companies. |
| Company type | Educational institutions, research institutes, government-linked organizations, private AI companies | Creates a balanced target set around the event ecosystem. |
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "pattern recognition" OR "computer vision" OR "robot vision" OR "signal processing") AND (Professor OR "Lab Director" OR "Director of Research" OR Dean OR "IT Director" OR "Research Scientist") AND (China OR Fujian OR Xiamen OR APAC) with industry filters centered on Higher Education, Research, Computer Software, and Information Technology & Services.
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| AIPR 2026 Official Website | Official event website | Confirmed event name, Xiamen location, country, official dates of September 18–20, 2026, organizer, co-sponsors, conference tracks, important deadlines, publication route, and venue identity. | High |
| AIPR Venue Page | Official event subpage | Confirmed Huaqiao University as venue and address: No.668 Jimei Avenue, Xiamen, Fujian, China 361021. | High |
| AIPR History / Publication Information on Official Site | Official historical reference | Verified prior edition continuity: Beijing 2018, Beijing 2019, virtual 2020–2022, Xiamen 2023 and 2024, Quanzhou 2025; also confirms indexed publication positioning. | High |
Verification note: The supplied official website content superseded conflicting date information in the prompt. This report therefore uses the organizer-confirmed event dates of September 18–20, 2026. The event is suitable for targeted B2B research and academic account-based outreach, but not ideal for large-scale attendee list building from public sources because attendee volume and organization-level attendance disclosure are limited.
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Tell us your work email and our AI instantly builds a buyer list matched to 2026 9th International Conference on Artificial Intelligence and Pattern Recognition (AIPR 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
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