Artificial Intelligence and Machine Learning for Open-world Novelty

Preface<br>Ganesh Chandra Deka<br>1. AI and Machine Learning for Real-world problems<br>Hamed Nozari, Agnieszka Szmelter-Jarosz and Javid Ghahremani<br>2. Graph Neural Network for learning complex problems<br>Chethana C<br>3. Adaptive Software platform architecture for Aerial Vehicle Safety Levels in real-world applications<br>Rakesh Shrestha, Rojeena Bajracharya and Shiho Kim<br>4. OODA Loop for Learning Open-world Novelty Problems<br>Pamul Yadav and Shiho Kim<br>5. Privacy-Aware Crowd Counting Methods for Real-World Environment<br>Sang Ho Lee, Kyuho Jeong and Shiho Kim<br>6. AI and Machine Learning for 3D Computer Vision Applications in Open-world<br>Kwanghoon Sohn<br>7. PIM Hardware accelerators for real-world problems<br>Dohyun Kim, Junghwan Choi and Shiho Kim<br>8. Irregular Situations in Real-World Intelligent Systems<br>Ashutosh Mishra and Shiho Kim<br>9. Offline Reinforcement Learning Methods for Real-world Problems<br>Taewoo Kim, Shiho Kim and Ho Suk<br>10. Addressing Uncertainty Challenges for Autonomous Driving in Real-World Environments<br>Ho Suk, Taewoo Kim, Yerin Lee and Shiho Kim