-
Applications and a Three-dimensional Desktop Environment for an Immersive Virtual Reality System
We developed an application launcher called Multiverse for scientific vi...
read it
-
Mixing realities for sketch retrieval in Virtual Reality
Drawing tools for Virtual Reality (VR) enable users to model 3D designs ...
read it
-
AeroVR: Immersive Visualization System for Aerospace Design
One of today's most propitious immersive technologies is virtual reality...
read it
-
Emotion visualization in Virtual Reality: An integrative review
A cluster of research in Human-Computer Interaction (HCI) suggests that ...
read it
-
A Review of Deep Learning Approaches to EEG-Based Classification of Cybersickness in Virtual Reality
Cybersickness is an unpleasant side effect of exposure to a virtual real...
read it
-
Post-processing of Engineering Analysis Results for Visualization in VR Systems
The applicability of Virtual Reality for evaluating engineering analysis...
read it
-
3D Face Reconstruction with Region Based Best Fit Blending Using Mobile Phone for Virtual Reality Based Social Media
The use of virtual reality (VR) is exponentially increasing and due to t...
read it
Deep Learning Development Environment in Virtual Reality
Virtual reality (VR) offers immersive visualization and intuitive interaction. We leverage VR to enable any biomedical professional to deploy a deep learning (DL) model for image classification. While DL models can be powerful tools for data analysis, they are also challenging to understand and develop. To make deep learning more accessible and intuitive, we have built a virtual reality-based DL development environment. Within our environment, the user can move tangible objects to construct a neural network only using their hands. Our software automatically translates these configurations into a trainable model and then reports its resulting accuracy on a test dataset in real-time. Furthermore, we have enriched the virtual objects with visualizations of the model's components such that users can achieve insight about the DL models that they are developing. With this approach, we bridge the gap between professionals in different fields of expertise while offering a novel perspective for model analysis and data interaction. We further suggest that techniques of development and visualization in deep learning can benefit by integrating virtual reality.
READ FULL TEXT
Comments
There are no comments yet.