چکیده مقاله
This paper introduces a method to enhance classi cation performance byintegrating blurred and Gaussian ltered data into the training process We demonstrate thee cacy of this approach through comprehensive experiments, revealing improved accuracy,robustness, and generalization compared to traditional boosting techniques Our ndingshighlight the potential of ltered data augmentation for creating diverse and informativetraining sets, contributing to more e ective adaptation to complex patterns within the data The proposed method not only enhances accuracy but also exhibits resilience to over tting,presenting a promising avenue for advancing classi cation methodologies
کلیدواژهها
نویسندگان
Saeedeh Kamjoo
Faculty of Mathematical Sciences, University of Tabriz, Tabriz, Iran Tahereh Majidi, and Mehrdad Lakestani
شیوه ارجاع
Kamjoo, Saeedeh,1403,Enhancing Multiclass Brain Tumor Classi cation through Boosting Data with Blurred and Gaussian Filters,1st International Biennial Conference of Artificial Intelligence and Data Science 2024,Bushehr
ارائهشده در
مجموعه مقالات اولین کنفرانس بین المللی دوسالانه هوش مصنوعی و علوم داده3 اردیبهشت 1403 · بوشهر