Summary of Methodology to Deploy Cnn-based Computer Vision Models on Immersive Wearable Devices, by Kaveh Malek (1) et al.
Methodology to Deploy CNN-Based Computer Vision Models on Immersive Wearable Devices
by Kaveh Malek, Fernando Moreu
First submitted to arxiv on: 28 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a method to deploy Convolutional Neural Network (CNN) models on Augmented Reality (AR) headsets. Current AR headsets lack the processing power to run complex image recognition tasks using CNNs, so researchers trained the models on computers and transferred the optimized weight matrices to the headset. The approach transforms image data and CNN layers into a one-dimensional format suitable for the AR platform. Using PyTorch and the LeNet-5 CNN model, the authors trained the model on the MNIST dataset and deployed it on a HoloLens AR headset. The results show that the model maintains an accuracy of approximately 98%, similar to its performance on a computer. This integration enables real-time image processing on AR headsets, allowing for human input into AI models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine wearing special glasses that can recognize objects and scenes in real time. That’s what this paper is about – making it possible for computers to work with humans using these “augmented reality” (AR) headsets. Right now, AR headsets aren’t powerful enough to do complex tasks like recognizing images. To fix this, researchers trained a special kind of computer program called a convolutional neural network (CNN) on a normal computer and then transferred the information to the AR headset. They tested it with pictures of handwritten numbers and found that it worked just as well as when run on a regular computer. This means we can now use these headsets to let humans work together with computers in real time. |
Keywords
* Artificial intelligence * Cnn * Neural network
