Application of transfer learning for object recognition using convolutional neural networks
In this work the transfer learning technique is used to create a computational tool that recognizes the objects of the automatic 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 oth...
- Autores:
-
López Sotelo, Jesús Alfonso
Salazar Gómez, Gustavo Andrés
Díaz Salazar, Nicolas
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2018
- Institución:
- Universidad Autónoma de Occidente
- Repositorio:
- RED: Repositorio Educativo Digital UAO
- Idioma:
- eng
- OAI Identifier:
- oai:red.uao.edu.co:10614/11409
- Palabra clave:
- Redes neuronales (Computadores)
Neural networks (Computer science)
Transfer learning
Softmax
Inception-V3
Tensorflow
Neural networks
Convolutional neural network
- Rights
- openAccess
- License
- Derechos Reservados - Universidad Autónoma de Occidente
| Summary: | In this work the transfer learning technique is used to create a computational tool that recognizes the objects of the automatic 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 |
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