An official invitation letter will be provided upon successful registration for your participation in the conference.
학술대회 참가 등록이 정상적으로 완료되면 공식 초청장이 발급됩니다.
Plenary, keynote and parallel sessions.
전체회의, 기조연설 및 분과 세션.
Connect with fellow researchers.
동료 연구자들과의 교류.
Digital certificate of participation.
디지털 참가 증명서 발급.
Official letter after successful registration.
등록 완료 후 공식 초청장 발급.
E-proceedings & resource materials.
전자 논문집 및 참고 자료.
Learn from leading experts & scholars.
저명한 전문가 및 학자들의 강연.
The conference's session tracks effectively support the following SDGs.
본 학술대회의 세션 트랙은 다음의 지속가능발전목표를 효과적으로 지원합니다.
This track focuses on the latest developments in supervised learning methodologies, emphasizing their applications across various domains. Researchers are invited to present innovative algorithms and case studies that demonstrate the effectiveness of these models.
This session explores the realm of unsupervised learning, highlighting novel clustering and dimensionality reduction techniques. Contributions that showcase real-world applications and theoretical advancements are encouraged.
This track delves into ensemble methods that combine multiple models to enhance predictive performance. Papers discussing novel ensemble strategies and their applications in various fields are welcome.
This session is dedicated to the exploration of regression models, focusing on new methodologies and their practical applications. Researchers are invited to share insights on model performance and validation techniques.
This track examines the theoretical foundations and practical applications of decision tree models in machine learning. Contributions that highlight advancements in interpretability and efficiency are particularly encouraged.
This session focuses on clustering methodologies and their applications in data analysis. Researchers are invited to present innovative approaches that address challenges in clustering high-dimensional data.
This track investigates the latest architectures in neural networks and their diverse applications across industries. Papers that discuss advancements in deep learning techniques and their impact on performance are encouraged.
This session highlights recent trends and innovations in deep learning models, emphasizing their transformative potential in various fields. Researchers are invited to present cutting-edge research that pushes the boundaries of deep learning.
This track addresses the critical aspects of model validation and performance evaluation in machine learning. Contributions that propose new metrics or frameworks for assessing model effectiveness are particularly welcome.
This session focuses on the application of machine learning models in healthcare analytics, exploring innovative solutions to improve patient outcomes. Researchers are encouraged to share case studies and empirical findings in this vital area.
This track examines the integration of machine learning techniques in financial modeling, including risk assessment and predictive analytics. Contributions that demonstrate the application of these models in real-world financial scenarios are highly encouraged.