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

11th - 12th June 2027 , Melbourne - Australia

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Call For Papers

The (ICDNNOT-27) 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:

  • 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

Assessment

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.

Publication

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

Submit Your Research Work Register Now