Essays about: "Återgivna bilder"

Found 3 essays containing the words Återgivna bilder.

  1. 1. Generate synthetic datasets and scenarios by learning from the real world

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

    Author : Paolo Berizzi; [2021]
    Keywords : Synthetic Data; Rendered Images; Computer Vision; Syntetiska data; återgivna bilder; datorsyn;

    Abstract : The modern paradigms of machine learning algorithms and artificial intelligence base their success on processing a large quantity of data. Nevertheless, data does not come for free, and it can sometimes be practically unfeasible to collect enough data to train machine learning models successfully. READ MORE

  2. 2. Deep Learning based Video Super- Resolution in Computer Generated Graphics

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

    Author : Vinit Jain; [2020]
    Keywords : Deep Learning; Convolutional Neural Networks; Video Super-Resolution; Computer Generated Graphics; Gaming.; Deep Learning; Convolutional Neural Networks; Video Super-Resolution; Computer Generated Graphics; Gaming.;

    Abstract : Super-Resolution is a widely studied problem in the field of computer vision, where the purpose is to increase the resolution of, or super-resolve, image data. In Video Super-Resolution, maintaining temporal coherence for consecutive video frames requires fusing information from multiple frames to super-resolve one frame. READ MORE

  3. 3. An empirical study on synthetic image generation techniques for object detectors

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

    Author : Claudio Salvatore Arcidiacono; [2018]
    Keywords : Object Detection; Synthetic Dataset; Deep Learning; Rendered Images; Computer Vision; Objektdetektion; Syntetisk datamängd; Djup inlärning; Återgivna bilder; Datorseende;

    Abstract : Convolutional Neural Networks are a very powerful machine learning tool that outperformed other techniques in image recognition tasks. The biggest drawback of this method is the massive amount of training data required, since producing training data for image recognition tasks is very labor intensive. READ MORE