Abstract Logo classification is crucial in various applications, including brand monitoring, copyright protection, and digital forensics. Traditional computer vision techniques face significant limitations, particularly in handling scale variations, occlusions, and background clutter. While deep learning models, particularly convolutional neural networks (CNNs), offer superior solutions, they often come with high computational costs, posing challenges for real-time deployment.