Hybrid Conferencee

International Conference on Visual Recognition and Machine Learning (ICVRML - 26)

12th - 13th June 2026 | Dubai, UAE
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Conference Brochure
Sample Full Paper
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Conference Notifications:

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Call for Papers Extended:
"The deadline for full paper submissions has been extended for the Research Plus International Conference in Dubai. Submit your research by today to participate in one of the top conferences."
Certificate of Presentation:
"Present your research and receive a Certificate of Presentation to recognise your valuable contribution to the conference."
Abstract Submissions Open:
"Abstract submissions for the Dubai event are now open! Don’t miss the chance to present your research. Submit now."
Networking with Global Experts:
"Engage with researchers and professionals from around the world at the Dubai conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Dubai, featuring global leaders and innovators sharing their knowledge."
Best Paper & Best Paper Presentation Award:
"Submit your paper and stand a chance to win the Best Paper Presentation Award. The winner will be recognized at the conference in Dubai."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICVRML aims to explore emerging trends and future directions in research and innovation. It provides a collaborative platform for researchers and professionals to share ideas that shape the future of their respective domains.

The conference highlights advancements in Vision Engineering, encouraging innovative, solution-oriented research that addresses global challenges and technological evolution.

Authors are invited to submit papers addressing, but not limited to, the following areas:

01
Deep learning for visual recognition
02
Image classification techniques and challenges
03
Object detection algorithms and applications
04
Visual data augmentation strategies
05
Transfer learning in visual recognition
06
Ethics in machine learning applications
07
Real-time visual recognition systems
08
Multi-modal visual data analysis
09
Human-computer interaction in visual systems
10
Visual recognition in autonomous vehicles
11
Face recognition and privacy concerns
12
3D object recognition techniques
13
Visual recognition in healthcare applications
14
Adversarial attacks on visual systems
15
Explainable AI in visual recognition
16
Visual recognition in social media
17
Benchmarking visual recognition datasets
18
Visual recognition for augmented reality
19
Challenges in large-scale visual datasets
20
Future trends in visual machine learning