2 citations · 3 across the 6 of their papers we have counts for
7 papers
On RGB-TIR Stereo Calibration under Extreme Resolution Asymmetry
Michał Król, Michał Salamonowicz, Władysław Skarbek +1
Accurate geometric calibration of RGB-thermal infrared (TIR) stereo camera systems is essential for multimodal building envelope analysis, yet remains challenging when low-cost the…
Camera Pose Revisited
Władysław Skarbek, Michał Salomonowicz, Michał Król
Estimating the position and orientation of a camera with respect to an observed scene is one of the central problems in computer vision, particularly in the context of camera calib…
Cross Entropy in Deep Learning of Classifiers Is Unnecessary -- ISBE Error is All You Need
Wladyslaw Skarbek
In deep learning classifiers, the cost function usually takes the form of a combination of SoftMax and CrossEntropy functions. The SoftMax unit transforms the scores predicted by t…
Multi-modal Residual Perceptron Network for Audio-Video Emotion Recognition
Xin Chang, Władysław Skarbek
Audio-Video Emotion Recognition is now attacked with Deep Neural Network modeling tools. In published papers, as a rule, the authors show only cases of the superiority in multi-mod…
Human Face Expressions from Images - 2D Face Geometry and 3D Face Local Motion versus Deep Neural Features
Rafal Pilarczyk, Xin Chang, Wladyslaw Skarbek
Several computer algorithms for recognition of visible human emotions are compared at the web camera scenario using CNN/MMOD face detector. The recognition refers to four face expr…
On Intra-Class Variance for Deep Learning of Classifiers
Rafal Pilarczyk, Wladyslaw Skarbek
A novel technique for deep learning of image classifiers is presented. The learned CNN models offer better separation of deep features (also known as embedded vectors) measured by…
Symbolic Tensor Neural Networks for Digital Media - from Tensor Processing via BNF Graph Rules to CREAMS Applications
Wladyslaw Skarbek
This tutorial material on Convolutional Neural Networks (CNN) and its applications in digital media research is based on the concept of Symbolic Tensor Neural Networks. The set of…