Results 261 to 270 of about 30,189 (295)
Using a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) to Classify Network Attacks
Information (Switzerland), 2020 An intrusion detection system (IDS) identifies whether the network traffic behavior is normal or abnormal or identifies the attack types. Recently, deep learning has emerged as a successful approach in IDSs, having a high accuracy rate with its ...
Pramita Sree Muhuri +2 more
exaly +2 more sources
OPT-RNN-DBSVM: OPTimal Recurrent Neural Network and Density-Based Support Vector Machine [PDF]
Mathematics, 2023 When implementing SVMs, two major problems are encountered: (a) the number of local minima of dual-SVM increases exponentially with the number of samples and (b) the computer storage memory required for a regular quadratic programming solver increases ...
Karim El Moutaouakil +2 more
exaly +2 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
RNN-Stega: Linguistic Steganography Based on Recurrent Neural Networks
IEEE Transactions on Information Forensics and Security, 2019Linguistic steganography based on text carrier auto-generation technology is a current topic with great promise and challenges. Limited by the text automatic generation technology or the corresponding text coding methods, the quality of the steganographic text generated by previous methods is inferior, which makes its imperceptibility unsatisfactory ...
Zhongliang Yang +4 more
openaire +1 more source
Detection of Ransomware Based on Recurrent Neural Network (RNN)
2021Ransomware, as a specific type of malignant programming, has as of late rose as a significant danger in PC security. With a capacity to bolt out client access to their substance, late ransomware assaults have caused serious effect at an individual and hierarchical level. Explicit auxiliary properties of ransomware can additionally improve the nature of
Saketh Kanumuri +3 more
openaire +1 more source
RECURRENT NEURAL NETWORKS (RNNS)
Recurrent Neural Networks (RNNs) are a specialized class of neural networks designed to process sequential data. Unlike traditional feedforward networks, RNNs utilize internal memory to maintain contextual information across time steps, making them ideal for tasks such as language modeling, time series forecasting, and speech recognition.Waseem Ahmad, Vishal Goyal, Dr Surender
openaire +1 more source
Recurrent Neural Networks (RNNs)
2019Recurrent neural networks (RNNs) are another specialized scheme of neural network architectures. RNNs are developed to solve learning problems where information about the past (i.e., past instants/events) is directly linked to making future predictions. Such sequential examples play up frequently in many real-world tasks such as language modeling where
openaire +1 more source
Mixing-RNN: A Recommendation Algorithm Based on Recurrent Neural Network
2019Collaborative filtering algorithms have been used by recommender systems for item (e.g., movie) recommendation. However, traditional collaborative filtering algorithms face challenges to provide accurate recommendation when users’ interest and context suddenly changed.
Enhan Liu +4 more
openaire +1 more source
Recurrent Neural Networks (RNNs)
2017Recurrent neural networks (RNNs) are models that were created to tackle problems within the scope of pattern recognition and are fundamentally built on the same concepts with respect to feed-forward MLPs. The difference is that although MLPs by definition have multiple layers, RNNs do not and instead have a directed cycle through which the inputs are ...
openaire +1 more source
Recurrent Neural Network (RNN) to Analyse Mental Behaviour in Social Media
International Journal of Software Science and Computational Intelligence, 2021A recent British study of people between the ages of 14 and 35 has shown that social media has a negative impact on mental health. The purpose of the paper is to detect people with mental disorders' behaviour in social media in order to help Twitter users in overcoming their mental health problems such as anxiety, phobia, depression, paranoia.
openaire +1 more source