In this paper, the concept of what we call AI-Box is presented. This concept is targeting small and medium-sized enterprises within the manufacturing industry sector. The AI-Box aims to bring technologies from Industry 4.0 to them, with the use of easy-to-use and versatile implementation. Preliminary experiments have been conducted at Aalborg University and at an industrial partner to solve vision tasks, which would be too expensive with conventional vision techniques. Moreover, three different convolutional neural networks were tested to find the best- suited architecture. The three networks tested were the simple AlexNet, the complex ResNeXt, and small and complex SqueezeNet. Our results show that it is possible to solve the classification problem in a few epochs. Furthermore, with the use of augmented data, the performance can be improved. Our preliminary results also showed that the simpler convolutional neural network architecture from AlexNet yields a better result when classifying simple data.
|Status||Udgivet - 2020|
|Begivenhed||30th International Conference on Flexible Automation and Intelligent Manufacturing - Athens, Grækenland|
Varighed: 15 jun. 2021 → 18 jun. 2021
|Konference||30th International Conference on Flexible Automation and Intelligent Manufacturing|
|Periode||15/06/2021 → 18/06/2021|