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Getting more from your datasets: Data augmentation, annotation and generative techniques
(XPERI Inc., 2018-05-18)
Deep Learning for embedded vision requires large datasets. Indeed the more varied training data is, the more accurate the trained network. But, acquiring and accurately annotating datasets costs time and money. This talk ...
Hybrid Semi-Parallel Deep Neural Networks (SPDNN) – example methodologies and use cases
(XPERI Inc., 2018-05-23)
Deep neural networks (DNNs) are typically trained on specific datasets, optimized with particular discriminating capabilities. Often several different DNN topologies are developed solving closely related aspects of a ...
Total variation-based dense depth from multicamera array
(Society of Photo-optical Instrumentation Engineers (SPIE), 2018-05-20)
Multicamera arrays are increasingly employed in both consumer and industrial applications, and various passive techniques are documented to estimate depth from such camera arrays. Current depth estimation methods provide ...
Semiparallel deep neural network hybrid architecture: first application on depth from monocular camera
(Society of Photo-optical Instrumentation Engineers (SPIE), 2018-08-07)
Deep neural networks have been applied to a wide range of problems in recent years. Convolutional neural network is applied to the problem of determining the depth from a single camera image (monocular depth). Eight different ...
Pushing the AI envelope: merging deep networks to accelerate edge artificial intelligence in consumer electronics devices and systems
(IEEE, 2018-02-08)
Deep neural networks (DNNs) are widely used by both academic and industry researchers to solve many long-standing problems in machine learning. There has been such a growth of research in this field, and it has been applied ...
Application of preconditioned alternating direction method of multipliers in depth from focal stack
(Society of Photo-optical Instrumentation Engineers (SPIE), 2018-04-06)
Postcapture refocusing effect in smartphone cameras is achievable using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the ...
The application of deep learning on depth from multi-array camera
(Institute of Electrical and Electronics Engineers, 2018-01-02)
Consumer-level multi-array cameras are a key enabling technology for next generation smartphones imaging systems. The present paper aims to analyze the accuracy of the depth estimation while using different camera combinations ...
Fake data - the future of advanced computer vision systems
(NUI Galway, 2018-10-22)
Recent research shows that Data Augmentation techniques and Synthetic Data can improve the accuracy and reduce the susceptibility of Deep Neural Networks to Adversarial Attacks. In this presentation we consider some of the ...
Latent space mapping for generation of object elements with corresponding data annotation
(Elsevier, 2018-10-25)
Deep neural generative models such as Variational Auto-Encoders (VAE) and Generative Adversarial Networks (GAN) give promising results in estimating the data distribution across a range of machine learning fields of ...
Gaze Visual - A graphical software tool for performance evaluation of eye gaze estimation systems
(Institute of Electrical and Electronics Engineers, 2018-08-15)
The concept of an open source software developed for all round performance evaluation of gaze tracking systems is presented. The capabilities of this software towards quantitative, statistical and visual analysis of gaze ...