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Visar resultat 1 - 5 av 598 uppsatser som matchar ovanstående sökkriterier.

  1. 1. "The Uphill AI Contract Challenge The Intra-Active Task: Reimagining Contracts"

    Magister-uppsats, Göteborgs universitet/Juridiska institutionen

    Författare :Filip Seiborg Wikström; [2024-02-16]
    Nyckelord :AI; Contract Law; New Materialism; Karen Barad; Intra-Action; Spacetimemattering; Ethico-Onto-Epistem-Ology; Cartesian-Newtonian paradigms; Antimethodology; Agency; Machine Learning;

    Sammanfattning : The traditional contract theories are insufficient to handle the challenges Artificial Intelligence (AI) is currently causing and will continue to cause to contract law. These challenges involve problems concerning the subject/object divide, agency, the embedding of legal code into interactive programming code, and ethical aspects concerning the transfer of power away from lawyers. LÄS MER

  3. 2. Data Augmentation for Object Detection using Deep Reinforcement Learning

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Axel Andersson; Nils Hallerfelt; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : Data augmentation is a concept which is used to improve machine learning models for computer vision tasks. It is usually done by firstly, defining a set of functions which transforms images and secondly, applying a random selection of these functions on the images. LÄS MER

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

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

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

    Sammanfattning : 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. LÄS MER

  5. 4. SCAFFOLDING MATHEMATICAL CONVERSATIONS:

    Master-uppsats, Göteborgs universitet/Institutionen för pedagogik, kommunikation och lärande

    Författare :Iuliana Mihaela Badica; [2023-10-10]
    Nyckelord :Interactive exhibit; mathematics; informal learning; science center; parent scaffolding; augmented reality;

    Sammanfattning : Purpose: This study aims to address the current research gap on interactive mathematics exhibits by investigating parents’ role in supporting their children’s mathematics learning using such displays. In addition to this, the study examines the design of an interactive exhibit and explores whether it can facilitate mathematics learning among parents and children. LÄS MER

  7. 5. IDENTIFICATION OF ENVIRONMENTALLY RELEVANT BENTHIC FORAMINIFERA FROM THE SKAGERRAK FJORDS BY DEEP LEARNING IMAGE MODELING

    Master-uppsats, Göteborgs universitet / Institutionen för biologi och miljövetenskap

    Författare :Marko Plavetic; [2023-06-26]
    Nyckelord :benthic foraminifera; deep learning; environmental monitoring; YOLOv7;

    Sammanfattning : Over the several past decades, there has been increasing interest in using foraminifera as environmental indicators for coastal marine environments. As compared to macrofauna, which are currently used in environmental studies, foraminifera offer several distinct advantages as bioindicators, including short generation times, a high number of individuals per small sample volume, hard and durable tests with high preservation potential, and low cost of sample extraction. LÄS MER