Think Different

  You might have experience in different types of image processing in deep learning [a part of machine learning]. One of them is reference learning. Transfer Learning (Reference Learning) in CNN Image Processing Transfer learning, also known as reference learning, is a machine learning technique where a model developed for one task is reused as the starting point for a model on a second task. In the context of Convolutional Neural Networks (CNNs) for image processing, transfer learning leverages pre-trained CNN models. Key Concepts Pre-trained models: Models trained on large, diverse image datasets (e.g., ImageNet). Feature extraction: Pre-trained models extract general features (edges, shapes, textures). Fine-tuning: Adapting pre-trained models to specific tasks through additional training. Benefits Reduced training time: Leverage existing knowledge. Improved accuracy: Pre-trained models provide a solid foundation. Smaller datasets: Effective with limited task-specific data. Popu...