Autonomous CNN (AutoCNN): a data-driven approach to network architecture determination

• Main Authors: Aradhya, Abhay M S, Ashfahani, Andri, Angelina, Fienny, Pratama, Mahardhika, de Mello, Rodrigo Fernandes, Sundaram, Suresh
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Evolving Intelligent Systems; Convolution Neural Networks
• Online Access: https://hdl.handle.net/10356/163879
• Institution: Nanyang Technological University

Designing a Convolutional Neural Networks (CNN) is a complex task and requires expert knowledge to optimize the performance and network architecture. In this paper, a novel data-driven approach is proposed to determine the architecture of CNN models. The proposed Autonomous Convolutional Neural Netw...