Essays about: "Semantic Networks"

Showing result 1 - 5 of 131 essays containing the words Semantic Networks.

  1. 1. Exploring the Depth-Performance Trade-Off : Applying Torch Pruning to YOLOv8 Models for Semantic Segmentation Tasks

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

    Author : Xinchen Wang; [2024]
    Keywords : Deep Learning; Semantic segmentation; Network optimization; Network pruning; Torch Pruning; YOLOv8; Network Depth; Djup lärning; Semantisk segmentering; Nätverksoptimering; Nätverksbeskärning; Fackelbeskärning; YOLOv8; Nätverksdjup;

    Abstract : In order to comprehend the environments from different aspects, a large variety of computer vision methods are developed to detect objects, classify objects or even segment them semantically. Semantic segmentation is growing in significance due to its broad applications in fields such as robotics, environmental understanding for virtual or augmented reality, and autonomous driving. READ MORE

  3. 2. Automatic Semantic Role Labelling (SRL) in Swedish

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : Lucy Yang Buhr; [2023-10-05]
    Keywords : Semantic role labelling; SRL; transfer learning; multi-task learning; multilingual transfer; T5; mT5;

    Abstract : In this paper, using deep learning networks, the first end-to-end semantic role labelling model (SRL) has been developed for Swedish texts. This Swedish SRL model can, with a given Swedish sentence, perform trigger identification, frame classification and argument extraction tasks automatically in a series. READ MORE

  4. 3. Network Orientation and Segmentation Refinement Using Machine Learning

    University essay from Linköpings universitet/Institutionen för medicinsk teknik

    Author : Michael Nilsson; Jonatan Kentson; [2023]
    Keywords : deep learning; semantic segmentation; orientation learning; road networks; retina networks;

    Abstract : Network mapping is used to extract the coordinates of a network's components in an image. Furthermore, machine learning algorithms have demonstrated their efficacy in advancing the field of network mapping across various domains, including mapping of road networks and blood vessel networks. READ MORE

  5. 4. Improved U-Net architecture for Crack Detection in Sand Moulds

    University essay from Högskolan i Gävle/Datavetenskap

    Author : Husain Ahmed; Hozan Bajo; [2023]
    Keywords : U-Net Architecture; Semantic Segmentation; Convolutional Neural Networks; Crack Detection;

    Abstract : The detection of cracks in sand moulds has long been a challenge for both safety and maintenance purposes. Traditional image processing techniques have been employed to identify and quantify these defects but have often proven to be inefficient, labour-intensive, and time-consuming. READ MORE

  6. 5. Hybrid Deep Learning approach for Lane Detection : Combining convolutional and transformer networks with a post-processing temporal information mechanism, for efficient road lane detection on a road image scene

    University essay from Jönköping University/Jönköping AI Lab (JAIL)

    Author : Dimitrios Zarogiannis; Stelio Bompai; [2023]
    Keywords : Lane Detection; CNN; Vision Transformer; Deep Learning; Semantic Segmentation; Computer Vision;

    Abstract : Lane detection is a crucial task in the field of autonomous driving and advanced driver assistance systems. In recent years, convolutional neural networks (CNNs) have been the primary approach for solving this problem. READ MORE