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Call for Paper

The ICDNNOT emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Computational Science,Data Science are explored to promote cross-domain knowledge exchange and collaborative innovation.

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

01
Optimization techniques for neural networks
02
Deep learning architectures for data analysis
03
Applications of neural networks in industry
04
Challenges in training deep neural networks
05
Transfer learning in deep learning models
06
Ethics of AI and neural networks
07
Real-world applications of optimization techniques
08
Visualization of neural network performance
09
Data-driven approaches in optimization research
10
Case studies of neural network applications
11
Future trends in deep learning optimization
12
Collaborative tools for neural network research
13
Impact of AI on optimization problems
14
Deep learning for image processing tasks
15
Neural networks in predictive modeling
16
Role of AI in decision-making processes
17
Data preprocessing for neural networks
18
Interdisciplinary approaches to optimization
19
Deep learning for time series analysis
20
Neural networks in healthcare applications

All submissions will undergo peer review to ensure quality and interdisciplinary relevance.

Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

👉 Register Now

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.

👉 Submit Your Research Work

Event Highlights

  • Keynote sessions by experienced speakers
  • Technical paper presentations across multiple topics
  • Opportunities for academic and professional networking
  • Discussions on current research developments

Contact Us

    Have questions about submission, registration, or publication? We’re happy to help.

  • Email: [email protected]
  • Phone:+91 9940952512

We look forward to your participation and contribution to the ASPHER Conference.