Essays about: "VGG16"

Showing result 1 - 5 of 37 essays containing the word VGG16.

  1. 1. AI-based image generation: The impact of fine-tuning on fake image detection

    University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

    Author : Nick Hagström; Anders Rydberg; [2024]
    Keywords : Fake image detection; LoRA; DreamBooth; Stable Diffusion; Image generation;

    Abstract : Machine learning-based image generation models such as Stable Diffusion are now capable of generating synthetic images that are difficult to distinguish from real images, which gives rise to a number of legal and ethical concerns. As a potential measure of mitigation, it is possible to train neural networks to detect the digital artifacts present in the images synthesized by many generative models. READ MORE

  3. 2. Exploring State-of-the-Art Machine Learning Methods for Quantifying Exercise-induced Muscle Fatigue

    University essay from Högskolan i Halmstad/Akademin för informationsteknologi

    Author : Abboud Afram; Danial Sarab Fard Sabet; [2023]
    Keywords : EMG; SEMG; STFT; CWT; SVM; CNN; GAN; DCGAN; BCE; SGD; deep learning; machine learning; muscle fatigue; DCGAN; spectrogram; CNN models; transfers learning; data augmentation; feature extraction;

    Abstract : Muscle fatigue is a severe problem for elite athletes, and this is due to the long resting times, which can vary. Various mechanisms can cause muscle fatigue which signifies that the specific muscle has reached its maximum force and cannot continue the task. READ MORE

  4. 3. Physiology-Guided Machine Learning for Improved Reliability of Non-Invasive Assessment of Pulmonary Hypertension

    University essay from Linköpings universitet/Avdelningen för medicinsk teknik

    Author : Frida Hermansson; [2023]
    Keywords : Pulmonary Hypertension; pulmonary hypertension; improving; physiological-guided; machine learning; neural networks; NN; artificial neural networks; non-invasive; PH; tricuspid regurgitation; peak tricuspid regurgitation velocity; tricuspid regurgitation velocity; right ventricular systolic pressure; VGG16; Unet; TR-CNN; CNN; pulmonell hypertension; förbättra; fysiologisk-guidning; neurala nätverk; trikuspidal regurgitation; maximal trikuspidal regurgitation; icke-invasivt;

    Abstract : Diagnosing pulmonary hypertension (PH) with right heart catheterization (RHC) is associated with a risk for complications and high expenses, leading to late diagnoses [1]. Transthoracic echocardiography can be used to assess non-invasive indicators for PH such as right ventricular systolic pressure (RVSP), which can be estimated by combining the peak tricuspid regurgitation velocity (TRV) with the estimated right arterial pressure (RAP). READ MORE

  5. 4. Multiclass Brain Tumour Tissue Classification on Histopathology Images Using Vision Transformers

    University essay from Linköpings universitet/Statistik och maskininlärning

    Author : Christoforos Spyretos; [2023]
    Keywords : medical imaging; deep learning; classification; CNN; Vision Transformer; glioblastoma; GBM; IvyGAP; brain tumour; histopathology; digital pathology; histology;

    Abstract : Histopathology refers to inspecting and analysing tissue samples under a microscope to identify and examine signs of diseases. The manual investigation procedure of histology slides by pathologists is time-consuming and susceptible to misconceptions. READ MORE

  6. 5. Fault Detection and Diagnosis for Automotive Camera using Unsupervised Learning

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

    Author : Ziyou Li; [2023]
    Keywords : Unsupervised Learning; Autoencoders; Image Clustering; Fault Detection and Diagnosis; Morphological Operations; Hardware-in-Loop; Advanced DriverAssistance System; Oövervakad inlärning; Autoencoders; Bildklustering; Felfindning och Diagnostik; Morfologiska Operationer; Hardware-in-Loop; Avancerade Förarassistanssystem;

    Abstract : This thesis aims to investigate a fault detection and diagnosis system for automotive cameras using unsupervised learning. 1) Can a front-looking wide-angle camera image dataset be created using Hardware-in-Loop (HIL) simulations? 2) Can an Adversarial Autoencoder (AAE) based unsupervised camera fault detection and diagnosis method be crafted for SPA2 Vehicle Control Unit (VCU) using an image dataset created using Hardware-inLoop? 3) Does using AAE surpass the performance of using Variational Autoencoder (VAE) for the unsupervised automotive camera fault diagnosis model? In the field of camera fault studies, automotive cameras stand out for its complex operational context, particularly in Advanced Driver-Assistance Systems (ADAS) applications. READ MORE