Registration summary
ConferenceICDNNOT
ModeStandard / Physical
ParticipationListener
Registration fee$175.00
Bank charges (5.8%)$10.15
Total payable$185.15
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICDNNOT conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Deep Neural Network Architectures +
This track focuses on the latest innovations in deep neural network designs and their applications in various fields. Researchers are invited to present their findings on novel architectures that enhance performance and efficiency.
02 Optimization Techniques in Machine Learning +
This session explores various optimization methods employed in machine learning to improve model accuracy and convergence. Contributions that discuss gradient descent variants and other optimization algorithms are particularly welcome.
03 Reinforcement Learning: Theory and Applications +
This track highlights the theoretical foundations and practical applications of reinforcement learning. Papers that investigate algorithmic advancements and case studies in real-world scenarios are encouraged.
04 Predictive Analytics in Big Data Environments +
This session addresses the challenges and methodologies associated with predictive analytics in big data contexts. Contributions that demonstrate the integration of deep learning techniques for predictive modeling are sought.
05 Simulation Techniques in Computational Science +
This track emphasizes the role of simulation in computational science, particularly in modeling complex systems. Researchers are invited to share their insights on simulation methodologies and their applications in various domains.
06 Data Mining Approaches Using Deep Learning +
This session focuses on the intersection of data mining and deep learning, exploring how advanced neural networks can enhance data extraction and analysis. Papers that present novel data mining techniques leveraging deep learning are encouraged.
07 Pattern Recognition with Neural Networks +
This track investigates the application of neural networks in pattern recognition tasks across diverse fields. Researchers are invited to present their work on innovative methods and their effectiveness in real-world applications.
08 Automation in Scientific Research through AI +
This session explores the role of artificial intelligence in automating scientific research processes. Contributions that demonstrate how AI can streamline research workflows and enhance productivity are welcome.
09 Gradient Descent and Its Variants in Optimization +
This track delves into gradient descent algorithms and their various adaptations for optimizing deep learning models. Researchers are encouraged to present empirical studies and theoretical advancements in this area.
10 Neural Architectures for Complex Problem Solving +
This session focuses on the development and application of neural architectures designed to tackle complex problems in various domains. Papers that highlight innovative solutions and their impact on problem-solving are encouraged.
11 Interdisciplinary Applications of Deep Learning +
This track showcases interdisciplinary research that applies deep learning techniques across different scientific fields. Contributions that highlight collaborative efforts and novel applications are particularly welcome.
