Step into the forefront of AI innovation with this groundbreaking compilation of research presented at the prestigious ICANN 2023 conference. Authored by leading experts and practitioners, this book offers an unparalleled exploration of the latest developments in Artificial Neural Networks (ANNs) and Machine Learning (ML).
Spanning theory, algorithms, and applications, each chapter delves into the dynamic landscape of ANNs and ML, providing insights into cutting-edge methodologies, emerging trends, and real-world applications. From deep learning architectures to reinforcement learning paradigms, this collection encapsulates the state-of-the-art in AI research.
Key highlights include:
- In-depth analyses of neural network architectures and optimization techniques.
- Advances in transfer learning, federated learning, and self-supervised learning.
- Case studies showcasing the transformative impact of ANNs across diverse domains, including healthcare, finance, and autonomous systems.
- Discussions on the intersection of AI ethics, fairness, and accountability.
- Perspectives on the future directions of ANNs and ML in the era of AI-driven innovation.
Be the first to review “Artificial Neural Networks and Machine Learning ? ICANN 2023: 32nd International Conference on Artificial Neural Networks, Heraklion, Crete, Greece, September 26?29, 2023, Proceedings, Part VII”