Curriculum-guided PPO variants, multi-critic training, and LiDAR augmentation reduce collisions and accelerate convergence for nonholonomic robots operating in cluttered indoor spaces.
@article{Taheri2024DeepRL,title={Deep Reinforcement Learning with Enhanced PPO for Safe Mobile Robot Navigation},author={Taheri, H. and Hosseini, S. R.},year={2024},journal={arXiv preprint arXiv:2405.16266},url={https://arxiv.org/abs/2405.16266},}
arXiv
COVID-19 Detection Based on Blood Test Parameters using Various Artificial Intelligence Methods
K. Khanjani, S. R. Hosseini, H. taheri, and 2 more authors
Compares classical machine learning and deep models on routine blood test features to provide rapid COVID-19 screening guidance when radiology resources are constrained.
@article{Khanjani2024COVID-19,title={COVID-19 Detection Based on Blood Test Parameters using Various Artificial Intelligence Methods},author={Khanjani, K. and Hosseini, S. R. and taheri, H. and Shashaani, S. and Teshnehlab, M.},year={2024},journal={arXiv preprint arXiv:2404.02348},url={https://arxiv.org/abs/2404.02348},}
ENet-21: An Optimized Light CNN Structure for Lane Detection
Seyed Rasoul Hosseini, Hamid Taheri, and Mohammad Teshnehlab