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Treating Cat Phobia Using Virtual Reality
SE-B-09
Sivan Hava Senvetu; sivansa1@ac.sce.ac.il Nofar Duchan; nofardoc1@gmail.com
Advisor: Dr. Marina Kniazhansky
SCE - Shamoon College of Engineering, Ashdod
‘Gatophobia’ (fear of cats) is a type of specific phobia that can cause significant distress and avoidance. While exposure therapy is highly effective, many individuals fear direct confrontation with the phobic stimulus. Virtual reality (VR) offers a controlled, gradual exposure in a safe environment. Our project involves developing a VR-based system to treat gatophobia through customizable exposure to virtual cats in varied settings. Our system provides personalized treatment while ensuring user safety. We have created relevant visual environments and structured the exposure stages. This system is designed to support gradual desensitization, thus helping to reduce avoidance of direct encounters with the phobic stimulus.
Keywords: exposure therapy, gatophobia, therapeutic technology, VR, zoophobia
Real-Time Road Accident Detection System Using Deep Learning
SE-B-10
Nir Hazan; nirha1@ac.sce.ac.il David Darf; davidda6@ac.sce.ac.il
Advisor: Dr. Tammar Shrot
SCE - Shamoon College of Engineering, Ashdod
Road accidents remain one of the leading causes of death and injury worldwide; timely intervention can significantly reduce their impact. The goal of this project is to develop a deep learning-based system that detects road accidents in real time and alerts relevant authorities. We built a pipeline using “YOLO11m” to track relevant objects and extract spatial features. These features are processed and placed in a customized ‘long short-term memory’ LSTM model that detects road accidents and forwards them to our website for further inspection. Our project addresses an issue in road safety by offering an automated solution that reduces human dependency and shortens response time.
Keywords: accident detection, computer vision, deep learning, LSTM, “YOLO”
Book of Abstracts | 2025
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