Attention-emotion-enhanced convolutional LSTM for sentiment analysis
Long short-term memory (LSTM) neural networks and attention mechanism have been
widely used in sentiment representation learning and detection of texts. However, most of …
widely used in sentiment representation learning and detection of texts. However, most of …
Perception and navigation in autonomous systems in the era of learning: A survey
Autonomous systems possess the features of inferring their own state, understanding their
surroundings, and performing autonomous navigation. With the applications of learning …
surroundings, and performing autonomous navigation. With the applications of learning …
SafetyMed: a novel IoMT intrusion detection system using CNN-LSTM hybridization
The Internet of Medical Things (IoMT) has become an attractive playground to
cybercriminals because of its market worth and rapid growth. These devices have limited …
cybercriminals because of its market worth and rapid growth. These devices have limited …
Collaborative prediction and detection of DDoS attacks in edge computing: A deep learning-based approach with distributed SDN
Edge computing (EC) has greatly facilitated the deployment of networked services with fast
responses and low bandwidth, by deploying computing and storage at the network edge …
responses and low bandwidth, by deploying computing and storage at the network edge …
Qtt-dlstm: A cloud-edge-aided distributed lstm for cyber–physical–social big data
Cyber–physical–social systems (CPSS), an emerging cross-disciplinary research area,
combines cyber–physical systems (CPS) with social networking for the purpose of providing …
combines cyber–physical systems (CPS) with social networking for the purpose of providing …
Large language models for medicine: a survey
To address challenges in the digital economy's landscape of digital intelligence, large
language models (LLMs) have been developed. Improvements in computational power and …
language models (LLMs) have been developed. Improvements in computational power and …
Learning adversarial transformer for symbolic music generation
N Zhang - IEEE transactions on neural networks and learning …, 2020 - ieeexplore.ieee.org
Symbolic music generation is still an unsettled problem facing several challenges. The
complete music score is a quite long note sequence, which consists of multiple tracks with …
complete music score is a quite long note sequence, which consists of multiple tracks with …
Chaotic time series prediction of nonlinear systems based on various neural network models
Y Sun, L Zhang, M Yao - Chaos, Solitons & Fractals, 2023 - Elsevier
This paper discusses the chaos prediction of nonlinear systems using various neural
networks based on the modified substructure data-driven modeling architecture. In the …
networks based on the modified substructure data-driven modeling architecture. In the …
A dynamically stabilized recurrent neural network
This work proposes a novel recurrent neural network architecture, called the Dynamically
Stabilized Recurrent Neural Network (DSRNN). The developed DSRNN includes learnable …
Stabilized Recurrent Neural Network (DSRNN). The developed DSRNN includes learnable …
A standardized Project Gutenberg corpus for statistical analysis of natural language and quantitative linguistics
M Gerlach, F Font-Clos - Entropy, 2020 - mdpi.com
The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical
analysis of language for more than 25 years. However, in contrast to other major linguistic …
analysis of language for more than 25 years. However, in contrast to other major linguistic …