Lecture notes
Signals and Systems 1. (in Hungarian)
Experimental physics 1. (in Hungarian)
Presentations
Object detection
(PDF)
Tutorial: Contrastive learning for unpaired image-to-image translation
(PDF)
Tutorial: Automated driving feature validation
(PDF)
Programs, source codes
SPF-IQA
: No-reference image quality assessment based on the fusion of statistical and perceptual features (MATLAB)
GSF-IQA
: No-reference image quality assessment with global statistical features (MATLAB)
MultiGAP-NRIQA
: Multi-Pooled Inception Features for No-Reference Image Quality Assessment (MATLAB)
ActMapFeat
: A Combined Full-Reference Image Quality Assessment Method Based on Convolutional Activation Maps (MATLAB)
MSDF-IQA
: No-Reference Image Quality Assessment with Multi-Scale Orderless Pooling of Deep Features (MATLAB)
FDD-IQA
: Analysis of Benford's law for no-reference quality assessment of natural, screen-content, and synthetic images (MATLAB)
FDD+Perceptual-VQA
: No-reference video quality assessment based on Benford's law and perceptual features (MATLAB)
DF-CNN-IQA
: No-Reference Image Quality Assessment with Convolutional Neural Networks and Decision Fusion (Jupyter Notebook)
LGV
: Full-Reference Image Quality Assessment Based on Grünwald–Letnikov Derivative, Image Gradients, and Visual Saliency (MATLAB)
SWLGV
: Full-Reference Image Quality Assessment Based on Grünwald–Letnikov Derivative, Image Gradients, and Visual Saliency (MATLAB)
FLG-IQA
: No-Reference Quality Assessment of Authentically Distorted Images Based on Local and Global Features (MATLAB)
SG-ESSIM
: Saliency-Guided Local Full-Reference Image Quality Assessment (MATLAB)
LFD-IQA
: A Human Visual System Inspired No-Reference Image Quality Assessment Method Based on Local Feature Descriptors (MATLAB)
SGL-IQA
: No-Reference Image Quality Assessment Using the Statistics of Global and Local Image Features (MATLAB)
SSIM CNN
(MATLAB)
BLIINDER
(MATLAB)
CNN-SVR
: No-Reference Video Quality Assessment Based on the Temporal Pooling of Deep Features (MATLAB)
CNN-LSTM
: No-reference video quality assessment via pretrained CNN and LSTM networks (MATLAB)
JPEG2000 image quality
(MATLAB)
Autocorrelation with Wiener-Khinchin-theorem
(C++)
Gomoku
(MATLAB)
IIR and FIR filters
(MATLAB MEX)
Color reduction using k-Means
(MATLAB)
Color reduction using SOM
(MATLAB)
Color reduction using FCM
(MATLAB)
Image generation using GAN
(Python)
TRON
(MATLAB)
Visualization of ML algorithms
(R)
Water rendering
(C++)
Pixelization
(C++)