Abstract
In this work, the transfer learning technique is used to create a computational tool that recognizes the objects of the automation laboratory of the Universidad Autónoma de Occidente in real time. As a pre-trained neural net, the Inception-V3 is used as a feature extractor in the images and on the other hand a softmax classifier is trained, this contains the classes that are going to be recognized. It was used Tensorflow platform with gpu in Python natively in Windows 10 and Opencv library for the use of video camera and other tools.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Castrillon, W., Alvarez, D., López, A.: Técnicas de extracción de características en imágenes para el reconocimiento de expresiones faciales. In: Scientia Et Technica, vol. XIV, no. 38, pp. 7–12 (2008)
Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., Torralba, A.: Object detectors emerge in deep scene CNNs (2015)
Brown, L.: Deep learning with GPUs (2015)
Loncomilla, P.: Deep learning: redes convolucionales (2016)
The data science blog. An intuitive explanation of convolutional neural networks. https://goo.gl/KdqfLV
Szegedy, C., et al.: Going deeper with convolutions (2014)
Alemi, A.: Improving inception and image classification in tensorflow (2016)
Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision (2015)
Tensorflow how to retrain inception´s final layer for new categories. https://www.tensorflow.org/tutorials/image_retraining#bottlenecks
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
López Sotelo, J.A., Díaz Salazar, N., Salazar Gomez, G.A. (2018). Application of Transfer Learning for Object Recognition Using Convolutional Neural Networks. In: Orjuela-Cañón, A., Figueroa-García, J., Arias-Londoño, J. (eds) Applications of Computational Intelligence. ColCACI 2018. Communications in Computer and Information Science, vol 833. Springer, Cham. https://doi.org/10.1007/978-3-030-03023-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-030-03023-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-03022-3
Online ISBN: 978-3-030-03023-0
eBook Packages: Computer ScienceComputer Science (R0)