Sökning: "Object segmentation"

Visar resultat 16 - 20 av 135 uppsatser innehållade orden Object segmentation.

  1. 16. Camera ISP optimization for computer vision tasks performed by deep neural networks

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

    Författare :Zhenghong Xiao; [2023]
    Nyckelord :Computer Vision; Image Signal Processing; DNN; Datorseende; bildsignalbehandling; DNN;

    Sammanfattning : This thesis aims to improve the performance of Deep Neural Networkss (DNNs) in Computer Vision tasks by optimizing the Image Signal Processor (ISP) parameters. The research investigates the use of simulated RAW images and the application of the DRL-ISP (Deep Reinforcement Learning for Image Signal Processor) method to enhance the accuracy and robustness of DNNs. LÄS MER

  3. 17. Exploration of performance evaluation metrics with deep-learning-based generic object detection for robot guidance systems

    Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Helena Gustafsson; [2023]
    Nyckelord :performance evaluation; robot guidance system; deep learning; object detection; instance segmentation;

    Sammanfattning : Robots are often used within the industry for automated tasks that are too dangerous, complex, or strenuous for humans, which leads to time and cost benefits. Robots can have an arm and a gripper to manipulate the world and sensors for eyes to be able to perceive the world. LÄS MER

  4. 18. TransRUnet: 2D Detection and Segmentation of Lymphoma Lesions in Full-Body PET-CT Images

    Master-uppsats, KTH/Medicinteknik och hälsosystem

    Författare :Lasse Stahnke; [2023]
    Nyckelord :Lymphoma; PET-CT; Deep Learning; CNN; Retina U-Net; Feature Pyramid Transformer; Detection; Segmentation; Lymfom; PET-CT; djupinlärning; CNN; Retina U-Net; Feature Pyramid Transformer; detektion; segmentering;

    Sammanfattning : Identification and localization of FDG-avid lymphoma lesions in PET-CT image volumes is of high importance for the diagnosis and monitoring of treatment progress in lymphoma patients. This process is tedious, time-consuming, and error-prone, due to large image volumes and the heterogeneity of lesions. LÄS MER

  5. 19. AATrackT: A deep learning network using attentions for tracking fast-moving and tiny objects : (A)ttention (A)ugmented - (Track)ing on (T)iny objects

    Master-uppsats, Jönköping University/JTH, Avdelningen för datavetenskap

    Författare :Fredric Lundberg Andersson; [2022]
    Nyckelord :Machine learning; Computer vision; Visual tracking; Attentions; Tiny fast-moving object;

    Sammanfattning : Recent advances in deep learning have made it possible to visually track objects from a video sequence. Moreover, as transformers got introduced in computer vision, new state-of-the-art performances were achieved in visual tracking. LÄS MER

  7. 20. A Deep Learning Based Approach to Object Recognition from LiDAR Data Along Swedish Railroads

    Master-uppsats, KTH/Fastigheter och byggande

    Författare :Egil Morast; [2022]
    Nyckelord :Deep learning; DGCNN; LiDAR; Object recognition; Railroad; Automatisation; Sweden; Point cloud; Djupinlärning; DGCNN; LiDAR; Objektigenkänning; Järnväg; Automatisering; Sverige; Punktmoln;

    Sammanfattning : Malfunction in the overhead contact line system is a common cause of disturbances in the train traffic in Sweden. Due to the preventive methods being inefficient, the Swedish Transport Administration has stated the need to develop the railroad maintenance services and has identified Artificial Intelligence (AI) as an important tool for this undertaking. LÄS MER