Adventures in data analysis: A systematic review of Deep Learning techniques for pattern recognition in cyber-physical-social systems

Z Amiri, A Heidari, NJ Navimipour, M Unal… - Multimedia Tools and …, 2024 - Springer
Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

Deep learning for iris recognition: A survey

K Nguyen, H Proença, F Alonso-Fernandez - ACM Computing Surveys, 2024 - dl.acm.org
In this survey, we provide a comprehensive review of more than 200 articles, technical
reports, and GitHub repositories published over the last 10 years on the recent …

A novel combined approach based on deep Autoencoder and deep classifiers for credit card fraud detection

H Fanai, H Abbasimehr - Expert Systems with Applications, 2023 - Elsevier
Due to the growth of e-commerce and online payment methods, the number of fraudulent
transactions has increased. Financial institutions with online payment systems must utilize …

LSTM-autoencoder-based anomaly detection for indoor air quality time-series data

Y Wei, J Jang-Jaccard, W Xu, F Sabrina… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Anomaly detection for indoor air quality (IAQ) data has become an important area of
research as the quality of air is closely related to human health and well-being. However …

Deep Q-learning based reinforcement learning approach for network intrusion detection

H Alavizadeh, H Alavizadeh, J Jang-Jaccard - Computers, 2022 - mdpi.com
The rise of the new generation of cyber threats demands more sophisticated and intelligent
cyber defense solutions equipped with autonomous agents capable of learning to make …

Customer profiling, segmentation, and sales prediction using AI in direct marketing

MSE Kasem, M Hamada, I Taj-Eddin - Neural Computing and Applications, 2024 - Springer
In the current business environment, where the customer is the primary focus, effective
communication between marketing and senior management is vital for success. Effective …

[HTML][HTML] DL-AMDet: Deep learning-based malware detector for android

AR Nasser, AM Hasan, AJ Humaidi - Intelligent Systems with Applications, 2024 - Elsevier
The Android operating system, with its market share leadership and open-source nature in
smartphones, has become the primary target of malware. However, detecting malicious …

A deep learning technique to detect distributed denial of service attacks in software-defined networks

WG Gadallah, HM Ibrahim, NM Omar - Computers & Security, 2024 - Elsevier
Abstract Software-Defined Network (SDN) is an established networking paradigm that
separates the control plane from the data plane. It has central network control, and …

A few-shot meta-learning based siamese neural network using entropy features for ransomware classification

J Zhu, J Jang-Jaccard, A Singh, I Welch, ALS Harith… - Computers & …, 2022 - Elsevier
Ransomware defense solutions that can quickly detect and classify different ransomware
classes to formulate rapid response plans have been in high demand in recent years …

Anomaly detection in Internet of medical Things with Blockchain from the perspective of deep neural network

J Wang, H **, J Chen, J Tan, K Zhong - Information Sciences, 2022 - Elsevier
IoMT technology has many advantages in healthcare system, such as optimizing the
medical service model, improving the efficiency of hospital operation and management, and …