Facial reflections in video conferencing feeds can be processed to eavesdrop on on-screen application activities at 99.32% accuracy across real devices and environments.
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A hybrid deep learning plus classical ML pipeline for waste image classification reaches up to 100% accuracy on TrashNet and a corrected household dataset while cutting feature dimensionality by over 95%.
citing papers explorer
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Turn Your Face Into An Attack Surface: Screen Attack Using Facial Reflections in Video Conferencing
Facial reflections in video conferencing feeds can be processed to eavesdrop on on-screen application activities at 99.32% accuracy across real devices and environments.
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Towards Accurate and Efficient Waste Image Classification: A Hybrid Deep Learning and Machine Learning Approach
A hybrid deep learning plus classical ML pipeline for waste image classification reaches up to 100% accuracy on TrashNet and a corrected household dataset while cutting feature dimensionality by over 95%.