Deep Learning Technique for Image Classification by Segmentation
Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems. Digital image processing allows the use of much more complex algorithms, and hence, can offer both more sophisticated performance at simple tasks, and the impl...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | México |
| Institución: | Instituto Tecnológico y de Estudios Superiores de Occidente |
| Repositorio: | Repositorio Institucional del ITESO |
| Idioma: | inglés |
| OAI Identifier: | oai:rei.iteso.mx:11117/7496 |
| Acceso en línea: | https://hdl.handle.net/11117/7496 |
| Access Level: | acceso abierto |
| Palabra clave: | Deep Learning Image Classification Image Segmentation |
| Sumario: | Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems. Digital image processing allows the use of much more complex algorithms, and hence, can offer both more sophisticated performance at simple tasks, and the implementation of methods that would be impossible by analogue means. In particular, digital image processing is a concrete application of, and a practical technology based on classification, localization, feature extraction and segmentation. The main objective is to understand the following challenges and identify a solution. |
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