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🚨 Open Research Position: Visual Anomaly Detection
We announce that there is an open research position in the RIML lab at Sharif University of Technology, supervised by Dr. Rohban.
🔍 Project Description:
Industrial inspection and quality control are among the most prominent applications of visual anomaly detection. In this context, the model is given a training set of solely normal samples to learn their distribution. During inference, any sample that deviates from this established normal distribution, should be recognized as an anomaly.
This project aims to improve the capabilities of existing models, allowing them to detect intricate anomalies that extend beyond conventional defects.
Introductory Paper:
Deep Industrial Image Anomaly Detection: A Survey
Requirements:
- Good understanding of deep learning concepts
- Fluency in Python, PyTorch
- Willingness to dedicate significant time
Submit your application here:
Application Form
Application Deadline:
2024/11/22 (23:59 UTC+3:30)
If you have any questions, contact:
@sehbeygi79
BY RIML Lab
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