Results 71 to 80 of about 3,768 (183)

Advancing Phishing Email Detection: A Comparative Study of Deep Learning Models

Sensors
Phishing is one of the most dangerous attacks targeting individuals, organizations, and nations. Although many traditional methods for email phishing detection exist, there is a need to improve accuracy and reduce false-positive rates.
Najwa Altwaijry, Isra Al-Turaiki, Reem Alotaibi, Fatimah Alakeel   +3 more
doaj   +1 more source

Fusion of deep recurrent neural network models and fuzzy decision support system for tweet sentiment analysis and classification

Automatika
With the advent of social media and networking, Tweet Sentiment Analysis (TSA) has become a significant methodology to extract useful information from the “X” platform users.
A. Sherin, S. Lokesh, S. N. Deepa, I. Jasmine Selvakumari Jeya   +3 more
doaj   +1 more source

Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification

Sensors
Brain–computer interfaces (BCIs) based on electroencephalography (EEG) enable neural activity interpretation for device control, with motor imagery (MI) serving as a key paradigm for decoding imagined movements.
Mouna Bouchane, Wei Guo, Shuojin Yang
doaj   +1 more source

Optimizing Question Answering Systems in Education: Addressing Domain-Specific Challenges

IEEE Access
Question Answering (QA) systems are increasingly essential in educational institutions, enhancing both learning and administrative processes by providing quick and accurate answers to user queries. However, existing systems often struggle with accurately
B. P. Swathi, M. Geetha, Girija Attigeri, M. V. Suhas, Srinithya Halaharvi   +4 more
doaj   +1 more source

A Multi-Scale Attention-Based Optimized Hybrid Deep Learning Model for Accurate Soil Salinity Mapping in Arid Oases

Land
Accurate soil salinization monitoring in arid oases is crucial for agricultural sustainability and ecological security. However, existing deep learning-based approaches often suffer from insufficient use of multi-scale information and inadequate modeling
Mingjie Qian, Hangyuan Liu, Haoyi Wang, Shun Hu, Weitao Chen   +4 more
doaj   +1 more source

A Predictive Maintenance Method for Shearer Key Parts Based on Qualitative and Quantitative Analysis of Monitoring Data

IEEE Access, 2019
Appropriate predictive maintenance is critical to shearers under poor working conditions to prevent major safety accidents and casualties. A predictive maintenance method for shearer key parts based on qualitative and quantitative analysis of monitoring ...
Hua Ding, Liangliang Yang, Zhaojian Yang
doaj   +1 more source

Retracted: Health Recognition Algorithm for Sports Training Based on Bi-GRU Neural Networks. [PDF]

J Healthc Eng, 2023
Healthcare Engineering JO.
europepmc   +1 more source

Abusive Language Detection in Urdu Text: Leveraging Deep Learning and Attention Mechanism

IEEE Access
The widespread use of the Internet and the tremendous growth of social media have enabled people to connect with each other worldwide. Individuals are free to express themselves online, sharing their photos, videos, and text messages globally.
Atif Khan, Abrar Ahmed, Salman Jan, Muhammad Bilal, Megat F. Zuhairi   +4 more
doaj   +1 more source

English Offensive Text Detection Using CNN Based Bi-GRU Model

2024 2nd International Conference on Information and Communication Technology (ICICT)
5 pages and 6 ...
Tonmoy Roy, Md Robiul Islam, Asif Ahmed Miazi, Anika Antara, Al Amin, Sunjim Hossain   +5 more
openaire   +2 more sources

Ship motion identification model based on enhanced Bi-LSTM

Zhongguo Jianchuan Yanjiu
ObjectiveAiming at the low prediction precision and poor adaptability of ship models based on the data-driven modeling strategy, an enhanced bi-directional long short-term memory (Bi-LSTM) model is proposed for the high-precision non-parametric modeling ...
Haozhe ZHANG, Zhibo YANG, Xuguo JIAO, Chengxing LÜ, Peng LEI   +4 more
doaj   +1 more source