Doctoral Candidate Ngô Dương Hà successfully defended her thesis on “Detection and Classification of Violent Behaviour among Students in Schools” at VNUHCM-University of Science, focusing on the development of a system using video data to detect and classify school violence. Her research, which involved creating the VSiSGU dataset and applying deep learning techniques, aimed to improve school safety by providing practical solutions for the detection and prevention of violence.

On 19th January, at Room F.205b, VNUHCM-University of Science, Doctoral Candidate Ngô Dương Hà successfully defended her doctoral thesis at the university level on the topic “Detection and Classification of Violent Behaviour among Students in Schools”.

The thesis, supervised by Associate Professor Ikuko Shimizu in the field of Mathematical Foundations for Computer Science, focused on developing a system to support the detection and classification of school violence based on video data and cameras. The research proposed two approaches: an indirect method of tracking object movement to identify the moving area, and a direct approach using classification from video. Notably, the thesis developed the VSiSGU dataset, which contains detailed labels for school violence behaviours, providing a foundation for applying deep learning methods such as VGG16, LSTM, and GRU to improve accuracy in detecting and classifying school violence. This contributed effectively to preventing violence in educational environments.

Key Findings of the Thesis

The thesis presented several novel results in prestigious journals and scientific conferences, with highlights including:

• A clear definition of school violence and the establishment of classification criteria based on images.
• The development of the VSiSGU dataset, specifically designed for school violence with reliable criteria.
• Improvements to the particle filter method, integrating motion direction and building an adjustment model to recover partially obscured objects during tracking.
• The combination of deep learning models (VGG16, LSTM, GRU) to enhance the accuracy of school violence classification with detailed hierarchical levels.
• The proposal of a frame reduction method in videos to improve efficiency and increase the practicality of implementation.
• The development of an integrated approach combining object tracking algorithms for each video frame with a regression neural network to analyse motion, enabling accurate classification of school violence behaviours.

These results were published in articles in reputable forums within the ISI and Scopus lists, affirming the research value of the thesis.

Applications and Future Research Directions

The thesis opened up several practical applications, including:

• A school violence detection and alert system that could be integrated into educational institutions to reduce violence and improve management quality.
• The application of surveillance technology in other fields such as public security, detection of abnormal behaviour in traffic, and in crowded areas.
• Data filtering and refinement to provide the user community with data, enhancing the feasibility of the system.
• New research directions in building datasets and developing deep learning models to optimise behaviour detection in complex situations.

However, several issues remained to be addressed, such as improving accuracy under noisy data conditions, handling object occlusion, and developing models adaptable to diverse contexts.

Doctoral Candidate Ngô Dương Hà’s thesis not only demonstrated her personal commitment to research but also made a significant contribution to raising awareness and providing solutions for school violence in modern educational environments.

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