traffic sign recognition
This is the collection of Indian Traffic Sign Detection Dataset. This can be used maily on Traffic Sign detection projects using YOLO. Dataset is in YOLO format. There are 1264 total images in this dataset fully annotated using Labelimg tool. Some augmented datas using techniques like blurring, mosaic etc.. are also present. The dataset has images in 3 different types of traffic signs in India. Dataset is annotated only as one class-Traffic Sign.
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This is the collection of Indian Traffic Sign Detection Dataset. This can be used maily on Traffic Sign detection projects using YOLO. Dataset is in YOLO format. There are 1264 total images in this dataset fully annotated using Labelimg tool. Some augmented datas using techniques like blurring, mosaic etc.. are also present. The dataset has images in 3 different types of traffic signs in India. Dataset is annotated only as one class-Traffic Sign.
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Cautionary traffic signs are of immense significance to traffic safety. In this study, a robust and optimal real-time approach to recognize the Indian Cautionary Traffic Signs(ICTS) is proposed. ICTS are all triangles with a white backdrop, a red border, and a black pattern. A dataset of 34,000 real-time images has been acquired under various environmental conditions and categorized into 40 distinct classes. Pre-processing techniques are used to transform RGB images to Gray-scale images and enhance contrast in images for superior performance.
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As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on the robustness of data-driven algorithms under diverse challenging conditions where trained models can possibly be depolyed.
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