Essays about: "förtränade modeller"

Showing result 1 - 5 of 39 essays containing the words förtränade modeller.

  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. Image-classification for Brain Tumor using Pre-trained Convolutional Neural Network

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

    Author : Bushra Alsabbagh; [2023]
    Keywords : Brain tumor; Deep learning; Convolutional Neural Network CNN ; diagnosis; Image classification; pre-trained models; dataset; economic impact.; Cancer; Hjärntumör; Artificiell intelligens AI ; djupinlärning; konvolutionellt neuralt nätverk CNN ; Diagnostik; Bildklassificering; förtränade modeller; dataset.;

    Abstract : Brain tumor is a disease characterized by uncontrolled growth of abnormal cells in the brain. The brain is responsible for regulating the functions of all other organs, hence, any atypical growth of cells in the brain can have severe implications for its functions. READ MORE

  4. 3. Deep Learning-Based Depth Estimation Models with Monocular SLAM : Impacts of Pure Rotational Movements on Scale Drift and Robustness

    University essay from Linköpings universitet/Datorseende

    Author : Daniel Bladh; [2023]
    Keywords : Deep Learning; Computer Vision; Monocular; SLAM; Depth Estimation;

    Abstract : This thesis explores the integration of deep learning-based depth estimation models with the ORB-SLAM3 framework to address challenges in monocular Simultaneous Localization and Mapping (SLAM), particularly focusing on pure rotational movements. The study investigates the viability of using pre-trained generic depth estimation networks, and hybrid combinations of these networks, to replace traditional depth sensors and improve scale accuracy in SLAM systems. READ MORE

  5. 4. Round-Trip Translation : A New Path for Automatic Program Repair using Large Language Models

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

    Author : Fernando Vallecillos Ruiz; [2023]
    Keywords : Automatic Program Repair; Software Engineering; Large Language Models; Round-Trip Translation; Neural Machine Translation; Automatisk programreparation; Mjukvaruutveckling; Stora språkmodeller; Tur och retur-översättning; Neural maskinöversättning;

    Abstract : Research shows that grammatical mistakes in a sentence can be corrected by machine translating it to another language and back. We investigate whether this correction capability of Large Language Models (LLMs) extends to Automatic Program Repair (APR), a software engineering task. READ MORE

  6. 5. Classification of Radar Emitters using Semi-Supervised Contrastive Learning

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

    Author : Tim Jonsson; [2023]
    Keywords : ;

    Abstract : Radar is a commonly used radio equipment in military and civilian settings for discovering and locating foreign objects. In a military context, pilots being discovered by radar could have fatal consequences. READ MORE