Reuse of a Deep Learning model for handwritten digit recognition
Machine Learning (ML) techniques have made significant advances in solving various problems, which has led to wide dissemination in their use and development. Currently there are different models that have achieved a high level of performance, which raises the question of what to do when we face a p...
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| Autores principales: | , , |
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| Formato: | Articulo |
| Lenguaje: | Español |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/168752 |
| Aporte de: |
| Sumario: | Machine Learning (ML) techniques have made significant advances in solving various problems, which has led to wide dissemination in their use and development. Currently there are different models that have achieved a high level of performance, which raises the question of what to do when we face a problem for which a very efficient model already exists. This scenario has, for some time, promoted the research and development of different techniques to reuse these models, instead of undertaking the design, implementation, and training of a new one, with all the effort that this entails. In this work, a classification problem is presented, and the reuse of a convolutional neural network is proposed with the objective of recognizing handwritten numbers. Likewise, the performance of the reused model has been evaluated. |
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