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(S1 IJECE 2019 Yasmine Khalid Zamil) Spam Image Email Filtering KNN SVM by Rendi Agus S is a document available to read on EtoBox.

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The paper proposes a spam image email filtering method using a combination of Support Vector Machine (SVM) and k-nearest neighbor (K-NN) techniques to improve detection accuracy, achieving approximately 98% effectiveness. It addresses the challenge of spam images that obscure content from text-based filters by utilizing texture features extracted from images through the Gray-Level Co-occurrence Matrix (GLCM). The study demonstrates the need for advanced filtering techniques in response to the increasing pre

Author

Rendi Agus S

Language

EN