AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
How to
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Banafa, A.
Artificial intelligence in action: Real-world applications and innovations Book
River Publishers, 2025, ISBN: 978-877004619-0 (ISBN); 978-877004620-6 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model
@book{banafa_artificial_2025,
title = {Artificial intelligence in action: Real-world applications and innovations},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000403587&partnerID=40&md5=4b0d94be48194a942b22bef63f36d3bf},
isbn = {978-877004619-0 (ISBN); 978-877004620-6 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {River Publishers},
series = {Artificial Intelligence in Action: Real-World Applications and Innovations},
abstract = {This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
2023
Lee, S.; Lee, H.; Lee, K.
Knowledge Generation Pipeline using LLM for Building 3D Object Knowledge Base Proceedings Article
In: Int. Conf. ICT Convergence, pp. 1303–1305, IEEE Computer Society, 2023, ISBN: 21621233 (ISSN); 979-835031327-7 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3D object, 3d-modeling, Augmented Reality, Data Mining, Knowledge Base, Knowledge based systems, Knowledge generations, Language Model, Metaverse, Metaverses, Multi-modal, MultiModal AI, Multimodal artificial intelligence, Pipelines, Virtual Reality, XR
@inproceedings{lee_knowledge_2023,
title = {Knowledge Generation Pipeline using LLM for Building 3D Object Knowledge Base},
author = {S. Lee and H. Lee and K. Lee},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184593202&doi=10.1109%2fICTC58733.2023.10392933&partnerID=40&md5=b877638607a04e5a31a2d5723af6e11b},
doi = {10.1109/ICTC58733.2023.10392933},
isbn = {21621233 (ISSN); 979-835031327-7 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {Int. Conf. ICT Convergence},
pages = {1303–1305},
publisher = {IEEE Computer Society},
abstract = {With the wide spread of XR(eXtended Reality) contents such as Metaverse and VR(Virtual Reality) / AR(Augmented Reality), the utilization and importance of 3D objects are increasing. In this paper, we describe a knowledge generation pipeline of 3D object for reuse of existing 3D objects and production of new 3D object using generative AI(Artificial Intelligence). 3D object knowledge includes not only the object itself data that are generated in object editing phase but the information for human to recognize and understand objects. The target 3D model for building knowledge is the space model of office for business Metaverse service and the model of objects composing the space. LLM(Large Language Model)-based multimodal AI was used to extract knowledge from 3D model in a systematic and automated way. We plan to expand the pipeline to utilize knowledge base for managing extracted knowledge and correcting errors occurred during the LLM process for the knowledge extraction. © 2023 IEEE.},
keywords = {3D modeling, 3D models, 3D object, 3d-modeling, Augmented Reality, Data Mining, Knowledge Base, Knowledge based systems, Knowledge generations, Language Model, Metaverse, Metaverses, Multi-modal, MultiModal AI, Multimodal artificial intelligence, Pipelines, Virtual Reality, XR},
pubstate = {published},
tppubtype = {inproceedings}
}