How can adversarial attacks impact deployed CNN models?

Feb 20, 2020 ... LeNet-5. LeNet-5 architecture is perhaps the most widely known CNN architecture. It was created by Yann LeCun in 1998 and widely used for ... Mar 31, 2021 ... This review attempts to provide a more comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field. CNN is one of the popular deep learning algorithms that recently gained popularity in the sector of hydrology and earth sciences (Panahi et al., 2020). The CNN ... Mar 9, 2024 ... A 1-dimensional convolutional neural network (1D CNN) model is developed to process deep learning of raw impedance signals for smart ... Jul 19, 2021 ... To learn how to train your first CNN with PyTorch, just keep reading. CNNs are a type of deep learning algorithm that can analyze and extract ... Oct 17, 2024 ... Deep learning-based anomaly detection using one-dimensional convolutional neural networks (1D CNN) in machine centers (MCT) and computer numerical control (CNC ... Nov 30, 2018 ... We have explored the potential of microscopy images of fluorescently labeled nuclei for the prediction of toxicity based on nucleus pattern recognition. Nov 28, 2022 ... In this study, different deep CNN models with multiple machine learning classifiers are investigated for monkeypox disease diagnosis using ... Dec 7, 2017 ... While people usually tend to simply resize any image into a square while training a CNN (for example, resnet takes a 224x224 square image), that looks ugly to ... Fundamental difference between convolutional neural network (CNN) and conventional machine learning is that, rather than using hand-crafted features, such as ...