Essays about: "artificiella neurala nätverk"

Showing result 11 - 15 of 109 essays containing the words artificiella neurala nätverk.

  1. 11. Forecasting and¨Optimization Models for Integrated PV-ESS Systems: : A Case Study at KTH Live-In Lab

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Mariana Flor Lopes; [2023]
    Keywords : Photovoltaic-Energy Storage System; Artificial Neural Networks; Self-Consumption; Linear Optimization; Cost Reduction; Solfångare-energilagringssystem; artificiella neurala nätverk; självkonsumtion; linjär optimering; kostnadsminskning;

    Abstract : With the ever-increasing adoption of renewable energy sources, the seamless integration of PV systems into existing grids becomes imperative. Therefore, this study investigates the integration of a PV-ESS system into sustainable urban living. READ MORE

  3. 12. Investigating Relations between Regularization and Weight Initialization in Artificial Neural Networks

    University essay from Lunds universitet/Beräkningsbiologi och biologisk fysik - Genomgår omorganisation

    Author : Rasmus Sjöö; [2022]
    Keywords : Artificial Neural Networks; L1 Regularization; L2 Regularization; Loss Function; Maximum Likelihood; Regularization Strength Synthetic Data Generation; Weight Initialization; Physics and Astronomy;

    Abstract : L2 regularization is a common method used to prevent overtraining in artificial neural networks. However, an issue with this method is that the regularization strength has to be properly adjusted for it to work as intended. This value is usually found by trial and error which can take some time, especially for larger networks. READ MORE

  4. 13. Deep neural networks for food waste analysis and classification : Subtraction-based methods for the case of data scarcity

    University essay from Uppsala universitet/Signaler och system

    Author : David Brunell; [2022]
    Keywords : Siamese network; convolutional neural network;

    Abstract : Machine learning generally requires large amounts of data, however data is often limited. On the whole the amount of data needed grows with the complexity of the problem to be solved. Utilising transfer learning, data augmentation and problem reduction, acceptable performance can be achieved with limited data for a multitude of tasks. READ MORE

  5. 14. Reducing the computational complexity of a CNN-based neural network used for partitioning in VVC compliant encoders

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

    Author : Saman Rassam; [2022]
    Keywords : Video Coding; VVC; Block Partitioning; VTM; ANN; CNN; Videkodning; VVC; Blockpartitionering; VTM; ANN; CNN;

    Abstract : Block partitioning is a computationally heavy step in the video coding process. Previously, this stage has been done using a full-search-esque algorithm. READ MORE

  6. 15. Classification and localization of extreme outliers in computer vision tasks in surveillance scenarios

    University essay from KTH/Hälsoinformatik och logistik

    Author : Tariq Daoud; Emanuel Zere Goitom; [2022]
    Keywords : Computer vision; deep learning; machine learning; artificial neural networks; convolutional neural networks; YOLOv4; Datorseende; djupinlärning; maskininlärning; artificiella neurala nätverk; konvolutionella neurala nätverk; YOLOv4;

    Abstract : Convolutional neural networks (CNN) have come a long way and can be trained toclassify many of the objects around us. Despite this, researchers do not fullyunderstand how CNN models learn features (edges, shapes, contours, etc.) fromdata. READ MORE