The International Conference on Artificial Neural Networks in IT (ICANNIT - 27) features a diverse range of session tracks designed to cover key research areas, emerging trends and interdisciplinary innovations within the field of Information Technology.
These sessions provide a platform for researchers, academicians, industry professionals and practitioners to present their work, exchange ideas and explore the advancements shaping the future of the domain.
Each track is carefully curated to encourage knowledge sharing, collaboration and meaningful discussion, and is aligned with the United Nations Sustainable Development Goals.
Submit Your AbstractInternational Conference on Artificial Neural Networks in IT (ICANNIT - 27) 设有多个分会主题,涵盖重要研究领域、前沿趋势与跨学科创新成果。
各分会主题为研究人员、学者、行业专家及实务工作者提供展示研究成果、交流学术思想、探讨领域发展的平台。
每个分会主题均经过精心设置,旨在促进知识共享、学术合作与深入研讨,并与联合国可持续发展目标(SDGs)保持一致。
提交摘要The session tracks of International Conference on Artificial Neural Networks in IT (ICANNIT - 27) support the following United Nations Sustainable Development Goals through research, collaboration and knowledge exchange.
本次会议的分会主题通过科研、合作与知识交流,支持以下联合国可持续发展目标。
Browse every track scheduled for this conference.
浏览本次会议的全部分会主题。
This track focuses on the latest advancements in deep learning methodologies and their applications in various IT domains. Researchers are encouraged to present innovative approaches that enhance model performance and efficiency.
SDG 9
SDG 12
This session explores the role of predictive modeling in optimizing IT systems and infrastructure. Contributions that demonstrate the impact of predictive analytics on decision-making processes are highly encouraged.
SDG 9
SDG 11
This track examines the integration of artificial intelligence in enhancing cybersecurity measures. Papers should discuss novel algorithms and frameworks that improve threat detection and response capabilities.
SDG 16
This session highlights the use of data analytics to optimize IT performance and resource management. Submissions should focus on case studies or methodologies that showcase effective data-driven strategies.
SDG 9
SDG 12
This track addresses the challenges and solutions associated with integrating artificial neural networks in cloud computing environments. Researchers are invited to present findings on scalability, efficiency, and performance improvements.
SDG 9
SDG 13
This session investigates the intersection of software development practices and machine learning techniques. Contributions should highlight best practices, tools, and frameworks that facilitate the incorporation of ML into software projects.
SDG 9
SDG 17
This track focuses on the application of computational intelligence techniques in network management. Papers should explore innovative solutions for network optimization, monitoring, and fault detection.
SDG 9
SDG 11
This session examines the relationship between IT governance frameworks and algorithm design. Contributions should discuss how governance principles can influence the development and deployment of algorithms in IT.
SDG 16
This track explores the role of automation in enhancing system reliability within IT infrastructures. Researchers are encouraged to present methodologies that demonstrate improved reliability through automated processes.
SDG 9
SDG 12
This session addresses the challenges of integrating IoT devices within existing IT frameworks and managing the resulting data. Contributions should focus on innovative solutions for data handling, security, and interoperability.
SDG 9
SDG 11
This track investigates various strategies for optimizing performance in IT services. Papers should present empirical studies or theoretical frameworks that contribute to the understanding of performance enhancement in service delivery.
SDG 9
SDG 12
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