Hybrid Conferencee

International Conference on Deep Learning for Image-Based Defect Detection (ICDLIBDD - 26)

26th - 27th June 2026 | Venice, Italy
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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 Venice. 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 Venice 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 Venice conference. Build collaborations and gain insights from leading experts."
Keynote Speaker Sessions:
"Don’t miss our Keynote Sessions in Venice, 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 Venice."
SDG-Inspired Conference Focus:
"Our conference will highlight research that addresses global sustainability, inclusive education, and solutions for environmental challenges."

Call for Paper

The ICDLIBDD 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 Data Science, 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 techniques for defect detection
02
Image processing in quality control
03
Data augmentation for defect recognition
04
Real-time defect detection systems
05
Machine learning for image classification
06
Data-driven approaches to defect analysis
07
Computer vision applications in manufacturing
08
Predictive analytics for defect prevention
09
Quality assurance using deep learning
10
Data ethics in image-based detection
11
Automated inspection systems and data
12
Data visualization for defect analysis
13
Collaborative robots in defect detection
14
Impact of AI on manufacturing quality
15
Future trends in defect detection technologies
16
Data management for image datasets
17
User engagement through defect analytics
18
Deep learning model optimization techniques
19
Data-driven insights for manufacturing defects
20
Integration of IoT in defect detection