Example code for our book Introduction to Artificial Intelligence for Security Professionals
Matlab implementation of facial landmark detection by deep multi-task learning
A facial recognition system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which facial recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database. It is also described as a Biometric Artificial Intelligence based application that can uniquely identify a person by analysing patterns based on the person's facial textures and shape. [1][better source needed] While initially a form of computer application, it has seen wider uses in recent times on mobile platforms and in other forms of technology, such as robotics. It is typically used as access control in security systems and can be compared to other biometrics such as fingerprint or eye iris recognition systems.[2] Although the accuracy of facial recognition system as a biometric technology is lower than iris recognition and fingerprint recognition, it is widely adopted due to its contactless and non-invasive process.[3] Recently, it has also become popular as a commercial identification and marketing tool.[4] Other applications include advanced human-computer interaction, video surveillance, automatic indexing of images, and video database, among others.
This implements training of popular model architectures, such as AlexNet, ResNet and VGG on the ImageNet dataset(Now we supported alexnet, vgg, resnet, squeezenet, densenet)
Natural language processing & computer vision models optimized for AWS
A collection of various deep learning architectures, models, and tips
A curated list of awesome Deep Learning tutorials, projects and communities.
ASR built in matlab using kNN classifier. Video added later with features extracted from mouth area.
