Sökning: "yolov3"

Visar resultat 1 - 5 av 41 uppsatser innehållade ordet yolov3.

  1. 1. Implementation of Bolt Detection and Visual-Inertial Localization Algorithm for Tightening Tool on SoC FPGA

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Muhammad Ihsan Al Hafiz; [2023]
    Nyckelord :Bolt detection; Visual-Inertial localization; System-on-Chip SoC ; Field-Programmable Gate Array FPGA ; Machine learning; Perspective-n-Points; Error-State Extended Kalman Filter ESEKF ; High-Level Synthesis HLS ; YOLO; Tightening tool; Bultdetektering; visuell-tröghetslokalisering; System-on-Chip SoC ; Field-Programmable Gate Array FPGA ; Machine Learning; Perspective-n-Points; Error-State Extended Kalman Filter ESEKF ; High-Level Synthesis HLS ; YOLO; åtdragningsverktyg;

    Sammanfattning : With the emergence of Industry 4.0, there is a pronounced emphasis on the necessity for enhanced flexibility in assembly processes. In the domain of bolt-tightening, this transition is evident. Tools are now required to navigate a variety of bolts and unpredictable tightening methodologies. LÄS MER

  3. 2. A Comparative study of YOLO and Haar Cascade algorithm for helmet and license plate detection of motorcycles

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Anusha Jayasree Mavilla Vari Palli; Vishnu Sai Medimi; [2022]
    Nyckelord :Accuracy; Haar Cascade Classifier; Helmet Detection; License Plate Detection; YOLOv3 algorithm.;

    Sammanfattning : Background: Every country has seen an increase in motorcycle accidents over the years due to social and economic differences as well as regional variations in transportation circumstances. One common mode of transportation for those in the middle class is a motorbike.  Every motorbike rider is legally required to wear a helmet when driving a bike. LÄS MER

  4. 3. DRIVING-SCENE IMAGE CLASSIFICATION USING DEEP LEARNING NETWORKS: YOLOV4 ALGORITHM

    Master-uppsats, Uppsala universitet/Statistiska institutionen

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

    Sammanfattning : 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. LÄS MER

  5. 4. Detecting Furniture in Images Based on Neural Network Models

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Jiayan Yang; [2022]
    Nyckelord :;

    Sammanfattning : Object detection is a challenging task that locates objects within an image or video and thenallows us to count and then track those objects. It is applied in a variety of ways, such as crowd counting, self-driving vehicles, video surveillance, face identification, and anomaly detection, and is utilized in a wide range of industries, including retail, sport, healthcare, marketing, interior design, agriculture, construction, and recreation. LÄS MER

  7. 5. En jämförande studie med hjälp av maskininlärning : Vilket neuralt nätverk är mest lämpad för objektdetektering?

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Rosa Ekström; Robin Nowakowski; [2022]
    Nyckelord :artificiell intelligens; CNN; neuralt nätverk; objektdetektering; objektlokalisering; jämförande studie;

    Sammanfattning : Artificiell intelligens, även kallat AI, har länge varit ett aktuellt ämne. Idag genomsyras hela samhället av artificiell intelligens, allt ifrån sökmotorer, servicetjänster, självkörande bilar till verktyg för att underlätta vissa arbeten. LÄS MER