Registration summary
ConferenceICDLTDA
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
ICDLTDA conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Deep Learning Algorithms +
This track focuses on the latest developments in deep learning algorithms, emphasizing their application in data analytics. Researchers are encouraged to present novel approaches that enhance the performance and efficiency of neural networks.
02 Neural Networks for Predictive Modeling +
This session explores the use of neural networks in predictive modeling across various domains. Contributions that demonstrate the effectiveness of these models in real-world applications are particularly welcome.
03 Feature Extraction Techniques in Data Science +
This track delves into innovative feature extraction methods that improve data representation for deep learning models. Papers that highlight the impact of these techniques on model performance are encouraged.
04 Convolutional Networks in Image and Signal Processing +
This session is dedicated to the application of convolutional networks in image and signal processing tasks. Researchers are invited to share their findings on how these networks can enhance pattern recognition and data interpretation.
05 Recurrent Networks for Time Series Analysis +
This track examines the role of recurrent networks in analyzing time series data. Contributions that showcase the ability of these networks to capture temporal dependencies and improve forecasting accuracy are sought.
06 Big Data Analytics with Machine Learning +
This session focuses on the integration of machine learning techniques in big data analytics. Papers that discuss scalable solutions and novel algorithms for handling large datasets are particularly encouraged.
07 Artificial Intelligence in Data-Driven Decision Making +
This track investigates the application of artificial intelligence in enhancing data-driven decision-making processes. Researchers are invited to present case studies and methodologies that illustrate the impact of AI on business and research outcomes.
08 Pattern Recognition Algorithms in Data Science +
This session highlights the development and application of pattern recognition algorithms in various data science contexts. Contributions that demonstrate innovative approaches to classification and clustering are welcome.
09 Ethical Considerations in Deep Learning Applications +
This track addresses the ethical implications of deploying deep learning techniques in data analytics. Papers that explore issues such as bias, transparency, and accountability in AI systems are encouraged.
10 Interdisciplinary Applications of Deep Learning +
This session showcases interdisciplinary applications of deep learning techniques across fields such as healthcare, finance, and social sciences. Researchers are invited to share insights on how deep learning can solve complex problems in diverse domains.
11 Future Trends in Deep Learning and Data Analytics +
This track looks ahead to emerging trends and future directions in deep learning and data analytics. Contributions that speculate on the next generation of techniques and their potential impact on the field are highly encouraged.
