Add to ORKGRecent 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 new tools that are available to build advanced virtual models that can be used to render large 2D training datasets suitable for training tomorrow\u27s advanced Computer Vision systems for deployment in consumer and smart-city use cases
Large amounts of data have become an essential requirement in the development of modern computer vis...
Realistic synthetic image data rendered from 3D models can be used to augment image sets and train i...
In recent years, deep learning has revolutionized computer vision and has been applied to a range of...
Deep learning allows computers to learn from observations, or else training data. Successful applica...
In the recent years deep learning has become more and more popular and it is applied in a variety o...
To ensure good performance, modern machine learning models typically require large amounts of qualit...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
Deep Learning for embedded vision requires large datasets. Indeed the more varied training data is, ...
Neural Networks are an effective technique in the field of Artificial Intelligence and in the field ...
An RGBZ synthetic dataset consisting of five object classes in a variety of virtual environments and...
In recent years, learning-based methods have become the dominant approach to solving computer vision...
Deep learning has improved the performance of many computer vision tasks. However, the features that...
Hierarchical neural networks with large numbers of layers are the state of the art for most computer...
Deep learning (DL) has revolutionized advanced digital picture processing, enabling significant adva...
Computer vision algorithms, such as those implementing object detection, are known to be susceptible...
Large amounts of data have become an essential requirement in the development of modern computer vis...
Realistic synthetic image data rendered from 3D models can be used to augment image sets and train i...
In recent years, deep learning has revolutionized computer vision and has been applied to a range of...
Deep learning allows computers to learn from observations, or else training data. Successful applica...
In the recent years deep learning has become more and more popular and it is applied in a variety o...
To ensure good performance, modern machine learning models typically require large amounts of qualit...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
Deep Learning for embedded vision requires large datasets. Indeed the more varied training data is, ...
Neural Networks are an effective technique in the field of Artificial Intelligence and in the field ...
An RGBZ synthetic dataset consisting of five object classes in a variety of virtual environments and...
In recent years, learning-based methods have become the dominant approach to solving computer vision...
Deep learning has improved the performance of many computer vision tasks. However, the features that...
Hierarchical neural networks with large numbers of layers are the state of the art for most computer...
Deep learning (DL) has revolutionized advanced digital picture processing, enabling significant adva...
Computer vision algorithms, such as those implementing object detection, are known to be susceptible...
Large amounts of data have become an essential requirement in the development of modern computer vis...
Realistic synthetic image data rendered from 3D models can be used to augment image sets and train i...
In recent years, deep learning has revolutionized computer vision and has been applied to a range of...