Add MISA project

content/projects/MISA/index.md

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+---
+# Project's title
+title: "MISA: Multi-lidar Intelligence for Smart City Applications"
+
+# Featured image used for thumbnail and banner at detail page
+featured_image: "aris_logo.jpg"
+
+# Short summary of the project
+summary: "The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks."
+
+# When project started and ended
+date_start: "2024-04-01T00:00:00Z"
+date_end: "2026-04-01T00:00:00Z"
+
+# Project_url
+project_url: "https://cris.cobiss.net/ecris/si/sl/project/22050"
+
+# Tags/Categories
+tags:
+- bilateral
+- graph neural networks
+- LiDAR
+- reinforcement learning
+- Japan
+- Slovenia
+- Shinkuma
+- sensor fusion
+---
+
+
+The MISA (Multi-lidar Intelligence for Smart City Applications) project aims to strengthen cooperation between the research group at Jozef Stefan Institute (JSI) in Slovenia and Shinkuma Lab at Shibaura Institute of Technology (SIT) in Tokyo, Japan. The scientific cooperation will focus on optimizing LiDAR (Light Detection and Ranging) sensors using machine learning, with JSI contributing expertise in time series analysis and SIT leveraging its experience with smart city applications. The collaboration will address two key challenges: enhancing LiDAR sensor fusion accuracy through deep reinforcement learning and mitigating sparsity in LiDAR data using Graph Neural Networks.
+
+
+## Funding
+
+Τhe MISA bilateral project receives funding from the Slovenian Research and Inovation Agency (ARIS) under Grant Agreement No. BI-JP/24-26-001.