A MediaPipe-based system assigns confidence scores from facial and hand cues, but the 90% accuracy claim is not backed by a sound evaluation.
IMVB7t: A Multi-Modal Model for Food Preferences based on Artificially Produced Traits
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abstract
Human behavior and interactions are profoundly influenced by visual stimuli present in their surroundings. This influence extends to various aspects of life, notably food consumption and selection. In our study, we employed various models to extract different attributes from the environmental images. Specifically, we identify five key attributes and employ an ensemble model IMVB7 based on five distinct models for some of their detection resulted 0.85 mark. In addition, we conducted surveys to discern patterns in food preferences in response to visual stimuli. Leveraging the insights gleaned from these surveys, we formulate recommendations using decision tree for dishes based on the amalgamation of identified attributes resulted IMVB7t 0.96 mark. This study serves as a foundational step, paving the way for further exploration of this interdisciplinary domain.
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Real-Time Confidence Detection through Facial Expressions and Hand Gestures
A MediaPipe-based system assigns confidence scores from facial and hand cues, but the 90% accuracy claim is not backed by a sound evaluation.