main webpage W Topic Deep Learning arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network tr… Article Open Deep Learning Open Article Page

Deep Learning

Branch of machine learning In machine learning, deep learning focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation learning. The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data. The adjective "deep" refers to the use of multiple layers (ranging from three to several hundred or thousands) in the network. Methods used can be supervised, semi-supervised or unsupervised. Some common deep learning network architectures include fully connected networks, deep belief networks, recurrent neural networks, convolutional neural networks, generative adversarial networks, transformers, and neural radiance fields. Critical Symbolic Virtual Narrative Open Deep Learning Open Article Page

Exploring foci of: arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network traffic encompasses various attack types, including new and evolving ones with minor changes. The data used to construct a predictive model for computer networks has a skewed class distribution and limited representation of attack types, which differ from real n… Open Article Page

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Explore Deep Learning W Topic Deep Learning arXiv (Cornell University) Deep Neural Networks based Meta-Learning for Network Intrusion Detection 2023 The digitization of different components of industry and inter-connectivity among indigenous networks have increased the risk of network attacks. Designing an intrusion detection system to ensure security of the industrial ecosystem is difficult as network tr… Article Critical Symbolic Virtual Narrative Open Deep Learning Open Article Page