Pre Trained Convolutional Neural Network

Pre-trained convolutional neural networks (CNNs) are foundational models in computer vision, leveraging massive datasets to learn powerful feature extractors that are then fine-tuned for specific tasks. Current research emphasizes efficient fine-tuning techniques, such as parameter-efficient methods and the exploration of different pre-trained backbones (e.g., EfficientNet, ResNet, ConvNeXt) for optimal performance across diverse domains and datasets, including medical imaging and remote sensing. This work is significant because it enables rapid adaptation of powerful models to new applications with limited data, improving accuracy and efficiency in various fields ranging from disease diagnosis to robotics.