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What is COCO

Enhancing Performance, Efficiency, and Security Through Complex Systems Control
This stands for Common Object in Context, which is a popular dataset used to train neural networks for object detection. It contains over 330 000 images with 80 object categories.
Published in Chapter:
Design of a Real-Time-Integrated System Based on Stereovision and YOLOv5 to Detect Objects
Oumayma Rachidi (ENSAM, Moulay Ismail University of Meknes, Morocco), Ed-Dahmani Chafik (ENSAM, Moulay Ismail University of Meknes, Morocco), and Badr Bououlid (ENSAM, Moulay Ismail University of Meknes, Morocco)
DOI: 10.4018/979-8-3693-0497-6.ch016
Abstract
Real-time object detection represents a major part in the development of advanced driver assistance systems (ADAS). Pedestrian detection has become one of the most important tasks in the field of object detection due to the increasing number of road accidents. This study concerns the design and implementation of a Raspberry Pi 4-based embedded stereovision system to detect 80 object classes including persons and estimate 3D distance for traffic safety. Stereo camera calibration and deep learning algorithms are discussed. The study shows the system's design and a custom stereo camera designed and built using 3D printer as well as the implementation of YOLOv5s in the Raspberry Pi 4. The object detector is trained on the context object detection task (COCO) 2020 dataset and was tested using one of the two cameras. The Raspberry Pi displays a live video including bounding boxes and the number of frames per second (FPS).
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More Results
Reconnoitering Generative Deep Learning Through Image Generation From Text
Common Objects in Context. A large-scale dataset used for applications like captioning, object detection, and segmentation.
Full Text Chapter Download: US $37.50 Add to Cart
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