Archive for June, 2024

CFP AISI25 20 – 22 Jan. 2025 Springer-Scopus

The 11th International Conference on Advanced Intelligent Systems and Informatics, (AISI’2025) The 11th International Conference on Advanced Intelligent Systems and Informatics, (AISI’2025) will be held on 20 – 22 Jan.  2025 in Port Said University, Egypt.  Conference website: https://egyptscience-srge.com/AISI2025/ We welcome your participation and contribution to the 11th International Conference on Advanced Intelligent Systems and Informatics (AISI’25) […]

CFP: IEEE International Symposium on Safety Security Rescue Robotics (SSRR), Nov. 12-14, 2024, in New York City, USA

;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration:none”> could you please distribute the CFP for IEEE SSRR 2024, see below, also PDF attached. Thank you!  Best regards,  Ivana Kruijff, SSRR 2024 programme co-chair IEEE_SSRR_2024_CFP.pdf

AIPAD: AI in Pancreatic Disease Detection and Diagnosis

Workshop on AI in Pancreatic Disease Detection and Diagnosis  Held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)” – October 10, 2024, Marrakesh (Morocco)   Web site: https://aipad-miccai.github.io/ 

ICSC Final CFP (Hybrid Conference Co-Sponsored by IEEE ): The Fourth Intelligent Cybersecurity Conference, 17–20 September, 2024 | Valencia, Spain.

The Fourth Intelligent Cybersecurity Conference (ICSC2024) Hybrid Event https://www.icsc-conference.org/2024/ 17–20 September, 2024 | Valencia, Spain. Technically Co-Sponsored by IEEE Spain Section ICSC 2024 CFP: In today’s world, connected systems, social networks, and mobile communications create a massive flow of data, which is prone to cyberattacks. This needs fast and accurate detection of cyber-attacks. Intelligent systems […]

Practical D2T 2024 @ INLG 2024 – First call for papers (data-to-text, neuro-symbolic, shared task)

The 2nd Workshop on Practical LLM-assisted Data-to-Text Generation (Practical D2T 2024) While large language models (LLMs) offer to become a viable alternative to traditional rule-based data-to-text (D2T) natural language generation (NLG), they still suffer from well-known neural model issues, such as lack of controllability and risk of producing harmful text. There are many potential solutions […]

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