Deep learning--based text classification: a comprehensive review
Deep learning--based models have surpassed classical machine learning--based
approaches in various text classification tasks, including sentiment analysis, news …
approaches in various text classification tasks, including sentiment analysis, news …
Sentiment analysis using deep learning architectures: a review
A Yadav, DK Vishwakarma - Artificial Intelligence Review, 2020 - Springer
Social media is a powerful source of communication among people to share their sentiments
in the form of opinions and views about any topic or article, which results in an enormous …
in the form of opinions and views about any topic or article, which results in an enormous …
A survey on text classification: From traditional to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
A survey on text classification: From shallow to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
[HTML][HTML] Capsule networks–a survey
Modern day computer vision tasks requires efficient solution to problems such as image
recognition, natural language processing, object detection, object segmentation and …
recognition, natural language processing, object detection, object segmentation and …
Attention-based BiLSTM fused CNN with gating mechanism model for Chinese long text classification
J Deng, L Cheng, Z Wang - Computer Speech & Language, 2021 - Elsevier
Neural networks have been widely used in the field of text classification, and have achieved
good results on various Chinese datasets. However, for long text classification, there are a …
good results on various Chinese datasets. However, for long text classification, there are a …
Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Framework for deep learning-based language models using multi-task learning in natural language understanding: A systematic literature review and future directions
Learning human languages is a difficult task for a computer. However, Deep Learning (DL)
techniques have enhanced performance significantly for almost all-natural language …
techniques have enhanced performance significantly for almost all-natural language …
COVID-19 outbreak: An ensemble pre-trained deep learning model for detecting informative tweets
SJ Malla, PJA Alphonse - Applied Soft Computing, 2021 - Elsevier
Abstract On 11 March 2020, the (WHO) World Health Organization declared COVID-19
(CoronaVirus Disease 2019) as a pandemic. A further crisis has manifested mass fear and …
(CoronaVirus Disease 2019) as a pandemic. A further crisis has manifested mass fear and …
Detecting fake news with capsule neural networks
Fake news has increased dramatically in social media in recent years. This has prompted
the need for effective fake news detection algorithms. Capsule neural networks have been …
the need for effective fake news detection algorithms. Capsule neural networks have been …