SNRI

(ICDNNOT - 27) | Hybrid Event
18th - 19th May 2027 | Comilla, Bangladesh

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International Conference on Deep Neural Networks and Optimization Techniques
(ICDNNOT - 27)

18th - 19th May 2027 Comilla, Bangladesh (Hybrid Event)

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Call for Paper

The ICDNNOT is committed to addressing global challenges through impactful research and sustainable solutions. It brings together researchers dedicated to advancing knowledge for societal benefit. Focusing on Computational Science, Data Science, the conference promotes research aligned with global development goals and long-term sustainability. Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Optimization techniques for neural networks
  • Deep learning architectures for data analysis
  • Applications of neural networks in industry
  • Challenges in training deep neural networks
  • Transfer learning in deep learning models
  • Ethics of AI and neural networks
  • Real-world applications of optimization techniques
  • Visualization of neural network performance
  • Data-driven approaches in optimization research
  • Case studies of neural network applications
  • Future trends in deep learning optimization
  • Collaborative tools for neural network research
  • Impact of AI on optimization problems
  • Deep learning for image processing tasks
  • Neural networks in predictive modeling
  • Role of AI in decision-making processes
  • Data preprocessing for neural networks
  • Interdisciplinary approaches to optimization
  • Deep learning for time series analysis
  • Neural networks in healthcare applications
Review & Publication

All submissions will be reviewed for their contribution to global impact and research quality. Accepted papers will be presented and considered for publication in reputed platforms.

Registration

Join participants from around the world by completing your registration and becoming part of a global research community.

Publication

Accepted papers will gain international exposure through conference presentations and publication opportunities.

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