Daniel Sikar:
SURF feature type, SVM classifier, creative mode. Job done
Daniel Sikar:
Convolutional Neural Network, Histogram of Gradients (Support Vector Machine) and Speeded-Up Robust Features (Support Vector Machine) classifiers
Daniel Sikar:
Misclassified face - Matlab vision.CascadeObjectDetector() III
Daniel Sikar:
Misclassified face - Matlab vision.CascadeObjectDetector() II
Daniel Sikar:
Augmentation - Blur plus 10 degree rotation
Daniel Sikar:
Misclassified face - Matlab vision.CascadeObjectDetector()
Daniel Sikar:
Image Augmentation - applying blur and rotation
Daniel Sikar:
Facial recognition - end game
Daniel Sikar:
Face masked Computer Vision class
Daniel Sikar:
Another facemasked MSc student
Daniel Sikar:
Added RGB facemask
Daniel Sikar:
Student with added facemask
Daniel Sikar:
MatLab matrix operations
Daniel Sikar:
Facemaks negative mask
Daniel Sikar:
100x100 pixel facemask mask
Daniel Sikar:
Facemask mask
Daniel Sikar:
Matlab mouth detection I
Daniel Sikar:
Matlab mouth detection II
Daniel Sikar:
Facemask negative mask
Daniel Sikar:
Facemask positive mask
Daniel Sikar:
Cropped facemask 100 x 66 pixels
Daniel Sikar:
Matlab image matrix operations
Daniel Sikar:
ConfusionMatrix Grayscale Image x HOG Features x Support Vector Machine 4 classes - 10x10 cell size
Daniel Sikar:
Histogram of Gradients 25x25 pixel cell size
Daniel Sikar:
Histogram of Gradients 25x25 pixel cell size II
Daniel Sikar:
Histogram of Gradients 10x10 pixel cell size
Daniel Sikar:
Histogram of Gradients 10x10 pixel cell size II
Daniel Sikar:
Histogram of Gradients 25x25 pixel cell size III
Daniel Sikar:
Confusion Matrix - Grayscale Image x SURF Features x Support Vector Machine - 16 classes - Accuracy = 0.7250
Daniel Sikar:
Grayscale Image x SURF x SVM Confusion Matrix, 3 classes
