TY  - CHAP
AU  - Clémence Alla Takam
AU  - Aurelle Tchagna Kouanou
AU  - Odette Samba
AU  - Thomas Mih Attia
AU  - Daniel Tchiotsop
ED  - Eneko Osaba
ED  - Esther Villar
ED  - Jesús L. Lobo
ED  - Ibai Laña
Y1  - 2021-05-04
PY  - 2021
T1  - Big Data Framework Using Spark Architecture for Dose Optimization Based on Deep Learning in Medical Imaging
N2  - Artificial Intelligence (AI) is widely known as a knowledge field that aims to make computers, robots, or products that mimic the way humans think. In the current scientific community, AI is an intensively studied area composed of multiple branches. Historically, machine learning and optimization are two of the most studied fronts thanks to the development of novel and challenging research topics such as transfer optimization, swarm robotics, and drift detection and adaptation to evolving conditions in real-time. This book collects radically new theoretical insights, reporting recent developments and evincing innovative applications regarding AI methods in all fields of knowledge. It also presents works focused on new paradigms and novel branches of AI science.
BT  - Artificial Intelligence
SP  - Ch. 2
UR  - https://doi.org/10.5772/intechopen.97746
DO  - 10.5772/intechopen.97746
SN  - 978-1-83962-388-2
PB  - IntechOpen
CY  - Rijeka
Y2  - 2024-04-26
ER  -