Essays about: "Semantisk Segmentering"

Showing result 16 - 20 of 57 essays containing the words Semantisk Segmentering.

  1. 16. Forest Growth And Volume Estimation Using Machine Learning

    University essay from Linköpings universitet/Datorseende

    Author : Gustav Dahmén; Erica Strand; [2022]
    Keywords : machine learning; computer vision; forest; object detection; semantic segmentation; forest inventory; forest type; maskinlärning; datorseende; skog; objektdetektion; semantisk segmentering; skogsinventering; skogstyp;

    Abstract : Estimation of forest parameters using remote sensing information could streamline the forest industry from a time and economic perspective. This thesis utilizes object detection and semantic segmentation to detect and classify individual trees from images over 3D models reconstructed from satellite images. READ MORE

  3. 17. Teaching an AI to recycle by looking at scrap metal : Semantic segmentation through self-supervised learning with transformers

    University essay from Linköpings universitet/Institutionen för datavetenskap

    Author : Edwin Forsberg; Carl Harris; [2022]
    Keywords : AI; self-supervised learning; SSL; Machine vision; ML; Semantic segmentation; Transformer; Swin-transformer; Barlow twins; DINO; SwAV; Recycling; AI; SSL; Datoreseende; maskininlärning; semantisk segmentering; Transformer; Swin-transformer; Barlow twins; DINO; SwAV; Återvinning;

    Abstract : Stena Recycling is one of the leading recycling companies in Sweden and at their facility in Halmstad, 300 tonnes of refuse are handled every day where aluminium is one of the most valuable materials they sort. Today, most of the sorting process is done automatically, but there are still parts of the refuse that are not correctly sorted. READ MORE

  4. 18. Point Cloud Data Augmentation for 4D Panoptic Segmentation

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

    Author : Wangkang Jin; [2022]
    Keywords : Point Cloud; Data Augmentation; 4D panoptic segmentation; Deep Learning; 3D Perception; Autonomous Driving; Punktmoln; Dataökning; 4D panoptisk segmentering; Djup lärning; 3D Perception; 3D Uppfattning; Autonom körning;

    Abstract : 4D panoptic segmentation is an emerging topic in the field of autonomous driving, which jointly tackles 3D semantic segmentation, 3D instance segmentation, and 3D multi-object tracking based on point cloud data. However, the difficulty of collection limits the size of existing point cloud datasets. READ MORE

  5. 19. Knowledge Distillation for Semantic Segmentation and Autonomous Driving. : Astudy on the influence of hyperparameters, initialization of a student network and the distillation method on the semantic segmentation of urban scenes.

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

    Author : Juan Sanchez Nieto; [2022]
    Keywords : Knowledge Distillation; Autonomous Driving; Semantic Segmentation; Cityscapes.; Kunskapsdestillation; Autonom Körning; Semantisk Segmentering; Stadslandskap.;

    Abstract : Reducing the size of a neural network whilst maintaining a comparable performance is an important problem to be solved since the constrictions on resources of small devices make it impossible to deploy large models in numerous real-life scenarios. A prominent example is autonomous driving, where computer vision tasks such as object detection and semantic segmentation need to be performed in real time by mobile devices. READ MORE

  6. 20. Semantic segmentation of off-road scenery on embedded hardware using transfer learning

    University essay from KTH/Mekatronik

    Author : Filip Elander; [2021]
    Keywords : Semantic Segmentation; forestry navigation; Deep Neural Network; autonomous navigation; residual neural network; Convolutional neural network; Semantisk Segmentering; Autonom Terrängnavigering; Residuala Nätverk; Konvolutionellt Neuralt Nätverk; Autonom navigering;

    Abstract : Real-time semantic scene understanding is a challenging computer vision task for autonomous vehicles. A limited amount of research has been done regarding forestry and off-road scene understanding, as the industry focuses on urban and on-road applications. READ MORE