Essays about: "image domain"

Showing result 21 - 25 of 189 essays containing the words image domain.

  1. 21. Unsupervised Domain Adaptation for Regressive Annotation : Using Domain-Adversarial Training on Eye Image Data for Pupil Detection

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

    Author : Erik Zetterström; [2023]
    Keywords : Neural networks; Deep learning; Convolutional neural networks; Transfer learning; Domain adaptation; Unsupervised training; Adversarial training; Keypoint detection; Regression; Neurala nätverk; Djupinlärning; Faltningsnätverk; Överförningsinlärning; Domänadaptering; Oövervakad inlärning; Motstående träning; Nyckelpunktsdetektion; Regression;

    Abstract : Machine learning has seen a rapid progress the last couple of decades, with more and more powerful neural network models continuously being presented. These neural networks require large amounts of data to train them. READ MORE

  3. 22. Instance Segmentation for Printed Circuit Board (PCB) Component Analysis : Exploring CNNs and Transformers for Component Detection on Printed Circuit Boards

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

    Author : Oliver Möller; [2023]
    Keywords : Deep Learning; Computer Vision; Image Processing; Object Detection; Instance Segmentation; Printed Circuit Board PCB ; Djupinlärning; Datorseende; Bildbehandling; Objektdetektering; Instanssegmentering; Tryckt kretskort;

    Abstract : In the intricate domain of Printed Circuit Boards (PCBs), object detection poses unique challenges, particularly given the broad size spectrum of components, ranging from a mere 2 pixels to several thousand pixels within a single high-resolution image, often averaging 4000x3000 pixels. Such resolutions are atypical in the realm of deep learning for computer vision, making the task even more demanding. READ MORE

  4. 23. How to Estimate Local Performance using Machine learning Engineering (HELP ME) : from log files to support guidance

    University essay from Linköpings universitet/Artificiell intelligens och integrerade datorsystem

    Author : Hugo Ekinge; [2023]
    Keywords : Machine learning; GRU; 1D-CNN; Transformer; log analysis; parameter estimation; regression; performance monitoring; deep learning; troubleshooting; support; Maskininlärning; GRU; 1D-CNN; Transformer; logganalys; parameteruppskattning; regression; prestandaövervakning; djupinlärning; felsökning; support;

    Abstract : As modern systems are becoming increasingly complex, they are also becoming more and more cumbersome to diagnose and fix when things go wrong. One domain where it is very important for machinery and equipment to stay functional is in the world of medical IT, where technology is used to improve healthcare for people all over the world. READ MORE

  5. 24. Classifying Google reCAPTCHA v2 - A study using transfer learning models and evaluating their robustness against adversarial perturbations

    University essay from Lunds universitet/Statistiska institutionen; Lunds universitet/Nationalekonomiska institutionen

    Author : Arvid Björklund; Marius Uogele; [2023]
    Keywords : reCAPTCHA; transfer learning; adversarial perturbations; convolutional neural network; Business and Economics;

    Abstract : This thesis seeks to examine the suitability and robustness of transfer learning models in creating an efficient reCAPTCHA v2 classifier, and further evaluates their performance against various adversarial attacks. Three models - DenseNet201, EfficientNetV2, and InceptionV3 - were trained and assessed, highlighting the applicability of transfer learning techniques in the classification of reCAPTCHA v2 challenges. READ MORE

  6. 25. Towards Large Scale Façade Parsing: A Deep Learning Pipeline Using Mask R-CNN

    University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

    Author : MOLA AYENEW; [2022-04-27]
    Keywords : pipeline; semi-automated; building facade; parsing; panorama imagery; Google Street view; mapillary; Mask R-CNN; deep learning; inference; rectilinear projection;

    Abstract : This thesis tries to find a methodology that create a working pipeline for building facade parsing, which allows to access large scale panorama imagery from Google Street View (GSV) and implement on deep learning models. We propose a semiautomated pipeline that integrates multiple systems for large-scale building facade parsing. READ MORE