| Journal: | Computación y sistemas |
| Database: | |
| System number: | 000560764 |
| ISSN: | 1405-5546 |
| Authors: | Ochoa Montiel, Rocío1 Sossa, Humberto2 Olague, Gustavo4 Sánchez López, Carlos1 |
| Institutions: | 1Universidad Autónoma de Tlaxcala, Facultad de Ciencias Básicas Ingeniería y Tecnología, México 2Instituto Politécnico Nacional, Centro de Investigación en Computación, México 3Tecnológico de Monterrey, Guadalajara, Jalisco. México 4Centro de Investigación Científica y de Educación Superior de Ensenada, México |
| Year: | 2023 |
| Season: | Ene-Mar |
| Volumen: | 27 |
| Number: | 1 |
| Pages: | 247-256 |
| Country: | México |
| Language: | Inglés |
| English abstract | In this work, an evolutionary vision approach is used for the automatic recognition of AML leukemia images. Unlike common approaches using convolutional neural networks, in the presented model the feature extraction process is transparent. Moreover, the structure of the obtained solutions is amenable to interpretation by a human user, which is a significant advantage over automatic recognition approaches based on deep neural networks. Experimental results show that the evolutionary vision approach can obtain satisfactory results on the AML leukemia recognition problem. |
| Keyword: | Leukemia, Automatic recognition, Evolutionary vision |
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