Cited by

Stress Recognition in Automobile Drivers (v1.0.0)

---

6 publications cite any version of this project or its primary paper, newest first.

• Predicting stress in automobile drivers using LSTMs with feature engineering
  Mehmet Yasin Ulukuş, Enes Ahmeti, Hatice Tekiner Mogulkoc. Soft Computing, 2025. Cites: dataset
• Design of Driver Stress Prediction Model with CNN-LSTM: Exploration of Feature Space using Genetic Programming
  Tingting Yang, Chenhao Xue, Jun Chen. International Joint Conference on Neural Networks (IJCNN), 2024. Cites: dataset
• Experimental Study on Emergency Psychophysiological and Behavioral Reactions to Coal Mining Accidents
  Xiangchun Li, Yuzhen Long, Shuhao Zhang et al. Applied Psychophysiology and Biofeedback, 2024. Cites: dataset
• Real-World Driver Stress Recognition and Diagnosis Based on Multimodal Deep Learning and Fuzzy EDAS Approaches
  Muhammad Amin, Khalil Ullah, Muhammad Asif et al. Diagnostics, 2023. Cites: dataset
• Driver stress levels detection system using hyperparameter optimization
  Mohammad Naim Rastgoo, Bahareh Nakisa, Andry Rakotonirainy et al. Journal of Intelligent Transportation Systems, 2022. Cites: dataset
• Review on Machine Learning Frameworks in Drivers’ Physiological Signal Analysis to Detect Stress
  Maryam Memar, Amin Mokaribolhassan, Amir Aminzadeh Ghavifekr. International Conference on Control, Instrumentation, and Automation, 2021. Cites: dataset

Citation data from OpenAlex, updated weekly. Papers that use the project without citing it may be missing.