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The base network, often referred to as the "backbone," is a foundational deep learning architecture used primarily for feature extraction. In the context of computer vision, it processes input images to produce a rich, multi-level representation that can be utilized by subsequent layers for tasks such as object detection, segmentation, or classification. Common backbone architectures include ResNet, VGG, and Inception networks, each offering varying depths and configurations to balance performance and computational efficiency. These pre-trained models serve as starting points, enabling faster training and improved accuracy in various machine learning applications 🚀🚀🚀
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