in this project we used image processing Technique to classify 9 class malwares our final goal is to reach an appropriate model with high accuracy and small size and computational cost
distributed-systems machine-learning cloud deep-learning pipeline malware image-processing ml embedded-systems transformer cloud-computing resnet dl smote malware-detection mobilenetv2 squeeznet malware-classification mobilevit cloudhierarchicaldnn
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Updated
Dec 3, 2024 - Jupyter Notebook