SIPL - Signal & Image Processing Laboratory

Neda Taghinezhad

As an Electrical Engineer passionate about Deep Learning and Computer Vision, I work as a Research Assistant at SIPL Lab, where my current research involves applying AI techniques to detect railway defects effectively. Building on my academic background—highlighted by my Master's thesis on anomaly detection in surveillance videos—I aim to leverage technology for innovative solutions that make an impact.

Education

• M.Sc. in Telecommunications Engineering, Shiraz University                            
• Thesis Title: Anomaly detection in crowded Surveillance Video Using deep learning.  Sep 2018 - Sep 2022
• B.Sc. in Electrical Engineering, Fasa University      Sep 2014 - Aug 2018

 Research Interests

• Deep Learning and Computer Vision
• Anomaly Detection and Activity Recognition Using Deep Learning
• Machine Learning and Pattern Recognition
• Digital Image and Video Processing
• Biomedical Signal and Image Processing
• Neural Radiance Fields (NeRFs)

Publication

• N. Taghinezhad and M. Yazdi, "A New Unsupervised Video Anomaly Detection Using Multi-Scale Feature Memorization and Multipath Temporal Information Prediction"  
• "Rail defect detection and classification using an effective machine learning method (currently under preparation for submission)." 

Teaching Experiences

• “Electrical Circuit 1”
  • In collaboration with Dr. Vahid Ghasemzadeh
• “Digital Image Processing” (2 years)
  • In collaboration with Prof. Mehran Yazdi
• “Advanced Engineering Mathematics”
  • In collaboration with Dr. Alireza Keshavarz Haddad

Software

• Python
• Deep learning frameworks (Pytorch, TensorFlow)
• MATLAB (m-file programming, Toolboxes, Simulink)
• Microsoft Office (Word, Excel, PowerPoint)
• Windows OS
• Linux (Ubuntu)

References

Dr Mehran Yazdi, Full professor of Shiraz University yazdi@shirazu.ac.ir