- author = "Mariana Alejandra {Chan Ley}",
- title = "Categorizacion robusta de imagenes de arte usando Brain Programming",
- title_en = "Robust art image categorization using Brain Programming",
- school = "Centro de Investigacion Cientifica y de Educacion Superior de Ensenada (CICESE), Baja California",
- year = "2022",
- address = "Mexico",
- keywords = "genetic algorithms, genetic programming, Brain Programming, Brain Programming, Programacion Genetica, Evolucion Piramidal, Corteza Visual Artificial, Clasificacion de imagenes, Brain Programming, Genetic programming, Pyramidal Evolution, Artificial virtual cortex, image classification, art media categorization, DCNN, AVC, SIFT",
-
URL = "
https://cicese.repositorioinstitucional.mx/jspui/handle/1007/3737",
-
URL = "
https://cicese.repositorioinstitucional.mx/jspui/bitstream/1007/3737/1/tesis_Mariana%20Alejandra%20Chan%20Ley_02%20ago%202022.pdf",
- size = "96 pages",
- abstract = "we describe an approach for automatic art media categorization. Nowadays, classifying artworks is often entrusted to people who are experts in the field; however, with the increasing volumes of digitised databases, the task becomes overwhelming. In this sense, automatic classification is necessary for organizing extensive digital collections. we follow a paradigm called Brain Programming (BP), a methodology inspired by the inner workings of the visual system in the brain. BP evolves computational models of the artificial visual cortex (AVC) to solve the challenging problem of natural image classification. We compare with the state-of-the-art classification methods and analyze the algorithm’s robustness against one of the most recurrent problems in classification algorithms, adversarial perturbations. We find that Brain Programming can obtain comparable performance to state-of-the-art methodologies without susceptibility to adversary attacks.",
-
notes = "In Spanish
AexNet, VGG, ResNet18, ResNet101.
Adversarial Patch v. Multiple Pixel Attack
Supervisor: Gustavo Olague Caballero",
