Essays about: "Pedestrian Detection"

Showing result 6 - 10 of 48 essays containing the words Pedestrian Detection.

  1. 6. DRIVING-SCENE IMAGE CLASSIFICATION USING DEEP LEARNING NETWORKS: YOLOV4 ALGORITHM

    University essay from Uppsala universitet/Statistiska institutionen

    Author : Muhammad Tamjid Rahman; [2022]
    Keywords : Machine learning; Convolutional neural network; Object detection; YOLO;

    Abstract : The objective of the thesis is to explore an approach of classifying and localizing different objects from driving-scene images using YOLOv4 algorithm trained on custom dataset.  YOLOv4, a one-stage object detection algorithm, aims to have better accuracy and speed. READ MORE

  3. 7. Multi-Camera Multi-Person Tracking Using Reinforcement Learning

    University essay from Lunds universitet/Matematik LTH

    Author : Axel Kärrholm; Linus Rickman; [2022]
    Keywords : Multi-Camera Multi-Object Tracking; Reinforcement Learning; Computer Vision; Machine Learning; Object Detection; Mathematics and Statistics;

    Abstract : The problem of multi-object-tracking in a network of cameras is an interesting and non-trivial problem. Given videos from a number of cameras the goal of Multi-Camera Multi-Object Tracking (MCMOT) is to find the full visible trajectory of each pedestrian from the videos as the pedestrians move across cameras. READ MORE

  4. 8. Pedestrian Multiple Object Tracking in Real-Time

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Samuel Wintzell; [2022]
    Keywords : Computer Vision; Deep Learning; Multiple Object Tracking; Object Detection; Person Re-identification; Datorseende; Djupinlärning; Spårning av Flera Objekt; Objektdetektering; Personidentifiering;

    Abstract : Multiple object tracking (MOT) is the task of detecting multiple objects in a scene and associating detections over time to form tracks. It is essential for many scene understanding tasks like surveillance, robotics and autonomous driving. READ MORE

  5. 9. Pedestrian Tracking by using Deep Neural Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Zeng Peng; [2021]
    Keywords : Deep Learning; Computer Vision; Multiple Object Tracking; Person Re- Identification; Object Detection;

    Abstract : This project aims at using deep learning to solve the pedestrian tracking problem for Autonomous driving usage. The research area is in the domain of computer vision and deep learning. Multi-Object Tracking (MOT) aims at tracking multiple targets simultaneously in a video data. READ MORE

  6. 10. Synthetic Data for Training and Evaluation of Critical Traffic Scenarios

    University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

    Author : Sofie Collin; [2021]
    Keywords : Machine Learning; Autonomous Driving; Synthetic Data; Critical Traffic Scenarios; Pedestrian Detection; Image Processing;

    Abstract : Modern camera-based vehicle safety systems heavily rely on machine learning and consequently require large amounts of training data to perform reliably. However, collecting and annotating the needed data is an extremely expensive and time-consuming process. In addition, it is exceptionally difficult to collect data that covers critical scenarios. READ MORE