SarwanShah/Distracted-Pedestrian-Classification-Using-CNNs-2020
Created a dataset of 1,300 images of distracted pedestrians and applied augmentation to expand it by 3x- 4x. Used Faster R-CNN to localize pedestrians and extract distracted individuals. Tested MLP, ANN (HOG), CNN, and VGG16 transfer learning, achieving 23%, 28%, 60%, and 62% accuracy, respectively.
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